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NEW FULL DB (2.4M)

   11 Anonymous
   3 Gene Kim
   2 Robert C Martin
   2 Pedro Domingos
   2 Michelle McNamara
   2 Jonathan Haidt
   2 Glenn Greenwald

*** NEWFULLDB 2.4M ***

1:Learning happens in the minds and souls, not in the databases of multiple-choice tests. ~ Ken Robinson
2:Companies that build and maintain databases in the cloud are snagging a growing slice of the $36 billion market. ~ Anonymous
3:Finally, most identity thefts occur when databases are not securely managed. So, my advice? Don’t ever end up in a database. ~ Joseph Fink
4:This is systems security for the Central Intelligence Agency. We would like to know why you are attempting to hack one of our classified databases. ~ Dan Brown
5:Databases, ontologies, and visual representations tie informatic genomes to the specific practices of computers, computational biology, and bioinformatics. ~ Anonymous
6:As you study computer science you develop this wonderful mental acumen, particularly with relational databases, systems analysis, and artificial intelligence. ~ Frederick Lenz
7:change’ is any activity that is physical, logical, or virtual to applications, databases, operating systems, networks, or hardware that could impact services being delivered. ~ Gene Kim
8:The reason why there is more pessimism about technology in Europe has to do with history, the use of databases to keep track of people in the camps, ecological disasters. ~ Evgeny Morozov
9:a ‘change’ is any activity that is physical, logical, or virtual to applications, databases, operating systems, networks, or hardware that could impact services being delivered. ~ Gene Kim
10:We’ve got one huge advantage—people believe what they see in databases. They’ve never learned the most important rule of cyberspace—computers don’t lie but liars can compute. ~ Terry Hayes
11:We also know that ISIS is recruiting who are not in those databases. So of course, we're going to miss them. And then we now learn that DHS says, "No, we can't check their social media." ~ Carly Fiorina
12:Next, we found numerous instances where developers have administrative access to production applications and databases. This violates the required segregation of duty required to prevent risk for fraud. ~ Gene Kim
13:Second, we're spending a huge amount of money on technology so that everyone can check out laptops and portable phones. We're spending more money to write our existing information into databases or onto CD-ROM. ~ Jay Chiat
14:Over time, managers and executives began using statistics and analysis to forecast the future, relying on databases and spreadsheets in much the same way ancient seers relied on tea leaves and goat entrails. The ~ Josh Kaufman
15:That is really not much different from the search engines that are being constructed today for users throughout the entire world to allow them to search through databases to access the information that they require. ~ Stephen Cambone
16:The quality of the information used in background checks is another cause for concern. One of the most common problems is that databases may include arrest records without any indication of whether a person was convicted. ~ Anonymous
17:it would be good to include staleness measurements in the standard set of metrics for databases. Eventual consistency is a deliberately vague guarantee, but for operability it’s important to be able to quantify “eventual. ~ Martin Kleppmann
18:If an NSA, FBI, CIA, DIA, etc analyst has access to query raw SIGINT databases, they can enter and get results for anything they want. Phone number, email, user id, cell phone handset id (IMEI), and so on - it's all the same. ~ Edward Snowden
19:By rendering the model in ASN.1, the NCBI created a system that combined objects (DNA sequences, protein sequences, references, sequence features) from a variety of databases and manipulated them all with a common set of software tools. ~ Anonymous
20:It is fitting that yesteryear's swashbuckling newspaper reporter has turned into today's solemn young sobersides nursing a glass of watered white wine after a day of toiling over computer databases in a smoke-free, noise-free newsroom. ~ Russell Baker
21:Database schemas are notoriously volatile, extremely concrete, and highly depended on. This is one reason why the interface between OO applications and databases is so difficult to manage, and why schema updates are generally painful. ~ Robert C Martin
22:The security of computers and the Internet is a horrible and dangerous mess. Every week we hear about breaches of databases of Social Security numbers and financial information and health records, and about critical infrastructure being insecure. ~ Matt Blaze
23:Beyond collecting comprehensive data about the online activities of hundreds of millions of people, X-KEYSCORE allows any NSA analyst to search the system’s databases by email address, telephone number, or identifying attributes such as an IP address. ~ Glenn Greenwald
24:One class of software, broadly known as analytical databases, dispenses with the relational model. Using innovations in on-disk storage and the use of distributed memory, analytical databases combine the flexibility of SQL with the speed of traditional OLAP systems. ~ Anonymous
25:Two of the NSA’s internal databases, code-named HAPPYFOOT and FASCIA, contain comprehensive location information of devices worldwide. The NSA uses the databases to track people’s movements, identify people who associate with people of interest, and target drone strikes. ~ Bruce Schneier
26:TeleAtlas,” or with the new satellite imagery services, “Images copyright Digital Globe.” These companies made substantial investments in their databases (NavTeq alone reportedly invested $750 million to build their database of street addresses and directions. Digital Globe ~ Tim O Reilly
27:the NSA databases “store information about your political views, your medical history, your intimate relationships and your activities online.” The agency claims this personal information won’t be abused, “but these documents show that the NSA probably defines ‘abuse’ very narrowly. ~ Glenn Greenwald
28:Having been blacklisted from working in television during the McCarthy era, I know the harm of government using private corporations to intrude into the lives of innocent Americans. When government uses the telephone companies to create massive databases of all our phone calls it has gone too far. ~ Studs Terkel
29:I’d just like to point out that I have a serious issue with the fact that we’ve sat here all night watching Eric hack into a hundred different secure and confidential websites and databases—including some really scary federal places—yet he refuses to get us free cable TV.”

“That’d be illegal. ~ Paige Tyler
30:The folks like myself that do this for a living, we were expecting a regular campaign had built the databases, done all the new social media, learned our lessons from [Barack] Obama whipping us twice on how to do voter contact, and then Donald Trump gets in it and turns it into a national election. ~ Melissa Harris Perry
31:In the past few years, police around the country have built up vast networks of cameras mounted on squad cars and posts that continuously take pictures of license plates, instantaneously enter the numbers in big computer databases and, as a result, quietly track the moves of millions of lawabiding Americans. You OK with that? ~ Anonymous
32:We get information in the mail, the regular postal mail, encrypted or not, vet it like a regular news organization, format it - which is sometimes something that's quite hard to do, when you're talking about giant databases of information - release it to the public and then defend ourselves against the inevitable legal and political attacks. ~ Julian Assange
33:From the perspective of the world's national security apparatuses you exist in several locations. You appear on property and income-tax registries, on passport and ID card databases. You show up on passenger manifests and telephone logs . . . You are fingertip swirls, facial ratios, dental records, voice patterns, spending trails, e-mail threads. ~ Mohsin Hamid
34:ZODB, for example, is similar to Python’s shelve but addresses many of its limitations, better supporting larger databases, concurrent updates, transaction processing, and automatic write-through on in-memory changes (shelves can cache objects and flush to disk at close time with their writeback option, but this has limitations: see other resources). ~ Mark Lutz
35:It's fascinating as we continue to innovate and lead the way in both the application space and the database space. In the very beginning, people said you couldn't make relational databases fast enough to be commercially viable. I thought we could, and we were the first to do it. But we took tremendous abuse until IBM said, "Oh yeah, this stuff is good." ~ Larry Ellison
36:In the information-processing ecosystem, learners are the superpredators. Databases, crawlers, indexers, and so on are the herbivores, patiently munging on endless fields of data. Statistical algorithms, online analytical processing, and so on are the predators. Herbivores are necessary, since without them the others couldn’t exist, but superpredators have a more exciting life. ~ Pedro Domingos
37:Writing in Library Journal, Ben Vershbow of the Institute for the Future of Book envisioned a digital ecology in which "parts of books will reference parts of other books. Books will be woven toghether out of components in remote databases and servers." Kevin Kelly wrote in The New York times Magagzine: "In the the new world of books, every bit informs another; every page reads all the other pages. ~ Jeff Jarvis
38:Um, because you're loopier than Flacky McPsycho, Mayor of Crazytown?"

"My databases show no record of this Crazytown of which you speak. A brain the size of an entire city burns inside me. My intelligence quotient is beyond the human scale. I would prefer if you did not refer to me in such a fashion."

"Oh, poor baby. Did I hurt the mass-murdering psychopathic artificial intelligence's feelings? ~ Amie Kaufman
39:The biochemist's approach pivots on concentration: find the protein by looking where it's most likely to be concentrated, and distill it out of the mix. The geneticist's approach, in contrast, pivots on information: find the gene by search for differences in "databases" created by two closely related cells and multiply the gene in bacteria via cloning. The biochemist distills forms; the gene cloner amplifies information. ~ Siddhartha Mukherjee
40:ART said, What does it want?

To kill all the humans, I answered.

I could feel ART metaphorically clutch its function. If there were no humans, there would be no crew to protect and no reason to do research and fill its databases. It said, That is irrational.

I know, I said, if the humans were dead, who would make the media? It was so outrageous, it sounded like something a human would say. ~ Martha Wells
41:Irritable bowel syndrome is a well-documented, little-publicized aftermath of diarrheal infections—especially severe or repeated bouts. If you talk to people who’ve recently been diagnosed with IBS, about a third of them will say that their symptoms began after a bad attack of food poisoning. Defense Department databases reveal a five-fold higher risk of IBS among men and women who suffered an acute diarrheal infection while deployed in the Middle East. ~ Mary Roach
42:Mitochondrial DNA is completely separate from a person’s regular DNA. It’s a bit of genetic material residing in the mitochondria of every cell in the body, and it is inherited unchanged from generation to generation, through the female line. That means all the descendants—male and female—of a particular woman will have identical mitochondrial DNA, which we call mtDNA. This kind of DNA is extremely useful in forensic work, and separate databases are kept of it. ~ Douglas Preston
43:It’s a completely different business model!” he exclaimed. “You need different skills, different people, different systems, different databases. There’s also less psychic satisfaction, less glamor, and less visibility compared to the glamor of the original equipment business. As in ‘I sold ten auto insurance policies today.’ Big deal! Or ‘I sold ten elevator maintenance contracts today.’ Big deal! You don’t get great press notices or win trips to Hawaii for that.” “No, ~ Adrian J Slywotzky
44:We need to take information, wherever it is stored, make our copies and share them with the world. We need to take stuff that's out of copyright and add it to the archive. We need to buy secret databases and put them on the Web. We need to download scientific journals and upload them to file sharing networks... With enough of us, around the world, we’ll not just send a strong message opposing the privatization of knowledge - we’ll make it a thing of the past. Will you join us? ~ Aaron Swartz
45:Which kinds of decisions are premature? Decisions that have nothing to do with the business requirements—the use cases—of the system. These include decisions about frameworks, databases, web servers, utility libraries, dependency injection, and the like. A good system architecture is one in which decisions like these are rendered ancillary and deferrable. A good system architecture does not depend on those decisions. A good system architecture allows those decisions to be made at the latest possible moment, without significant impact. ~ Robert C Martin
46:requires us to divide our attention between ever more emails, text messages, cellphone calls, video streams, and blinking banners, resulting, he argues, in lowered productivity and a distracted life devoid of meaning and depth. A similar point is made by Hal Crowther (2010: 108) in an essay in Granta: Though the educational potential of the Internet is limitless, it is becoming apparent that wired students use technology less to learn than to distract themselves from learning, and to take advantage of toxic shortcuts like research-paper databases and essay-writing websites. ~ Scott Thornbury
47:Although government officials have repeatedly said there is a rigorous process for making sure no one is unfairly placed in the databases, the guidelines acknowledge that all nominations of “known terrorists” are considered justified unless the National Counterterrorism Center has evidence to the contrary. In an April 2014 court filing, the government disclosed that there were 468,749 KST nominations in 2013, of which only 4,915 were rejected—a rate of about 1 percent.10 The rules appear to invert the legal principle of due process, defining nominations as “presumptively valid. ~ Jeremy Scahill
48:Databases of this type are interrogated in a language called SQL. You send them commands like the one shown here to interact with their stored information. Understanding how to manipulate these databases is subtle. The example command, for example, creates a “view”: a virtual database table that pulls together data from multiple existing tables, and that can then be addressed by the SQL commands like a standard table. When to create views and how to do so well is a tricky question, one of many that you must understand and master to tease reasonable results out of real-world databases. ~ Cal Newport
49:A similar concern about using the web to provide just-in-time information shows up among physicians arguing the future of medical education. Increasingly, and particularly while making a first diagnosis, physicians rely on handheld databases, what one philosopher calls “E-memory.” The physicians type in symptoms and the digital tool recommends a potential diagnosis and suggested course of treatment. Eighty-nine percent of medical residents regard one of these E-memory tools, UpToDate, as their first choice for answering clinical questions. But will this “just-in-time” and “just enough” information teach young doctors to organize their own ideas and draw their own conclusions? ~ Sherry Turkle
50:The old botanical metaphors for memory, with their emphasis on continual, indeterminate organic growth, are, it turns out, remarkably apt. In fact, they seem to be more fitting than our new, fashionably high-tech metaphors, which equate biological memory with the precisely defined bits of digital data stored in databases and processed by computer chips. Governed by highly variable biological signals, chemical, electrical, and genetic, every aspect of human memory—the way it’s formed, maintained, connected, recalled—has almost infinite gradations. Computer memory exists as simple binary bits—ones and zeros—that are processed through fixed circuits, which can be either open or closed but nothing in between. ~ Nicholas Carr
51:languages like Maya or Luxembourgish. Translation is no longer usually to or from English. Technology, far from replacing humans, is instead a tool that helps them keep up with surging demand for high-quality translation. “Translation memory” (TM) was the first big useful tool. Since the 1980s translators have been able to dip into vast TM databases containing whole sentences that have already been translated in a given language pair, helping them to speed up repetitive work, such as translating instruction manuals. “Machine translation” is the next step. Computers learn from huge databases of already-translated text to make ever-better guesses about how to render whole chunks from one language into another. Translators ~ Anonymous
52:In ordinary times—times here understood to mean whole geologic epochs—extinction takes place only very rarely, more rarely even than speciation, and it occurs at what’s known as the background extinction rate. This rate varies from one group of organisms to another; often it’s expressed in terms of extinctions per million species-years. Calculating the background extinction rate is a laborious task that entails combing through whole databases’ worth of fossils. For what’s probably the best-studied group, which is mammals, it’s been reckoned to be roughly .25 million species-years. This means that, since there are about fifty-five hundred mammal species wandering around today, at the background extinction rate you’d expect—once again very roughly—one species to disappear every seven hundred years. ~ Elizabeth Kolbert
53:A more welcome fellow traveler on the modern human diaspora from Africa may have been the dog, the first known domestic animal. There is evidence that Aurignacian people living in Goyet Cave, Belgium, already had large dogs accompanying them about 35,000 years ago. The dogs were anatomically distinct from wolves in their shorter and broader snout and dental proportions, and isotope data suggest that they, like the humans, were feeding off horses and wild cattle. Moreover, ancient dog DNA was obtained, which showed that the Belgian dogs were already genetically diverse and that their mitochondrial sequences could not be matched among the large databases of contemporary wolf and dog DNA. These findings are important because they suggest that dog domestication had already been under way well before 35,000 years ago. ~ Chris Stringer
54:retrieve? When it comes to databases, chances are you’ll need to retrieve your data as often than you’ll need to insert it. That’s where this chapter comes in: you’ll meet the powerful SELECT statement and learn how to gain access to that important information you’ve been putting in your tables. You’ll even learn how to use WHERE, AND, and OR to selectively get to your data and even avoid displaying the data that you don’t need. I’m a star! Date or no date? 54 A better SELECT 57 What the * is that? 58 How to query your data types 64 More punctuation problems 65 Unmatched single quotes 66 Single quotes are special characters 67 INSERT data with single quotes in it 68 SELECT specific columns to limit results 73 SELECT specific columns for faster results 73 Combining your queries 80 Finding numeric values 83 Smooth Comparison Operators ~ Anonymous
55:This is the truth: We are a nation accustomed to being afraid. If I’m being honest, not just with you but with myself, it’s not just the nation, and it’s not just something we’ve grown used to. It’s the world, and it’s an addiction. People crave fear. Fear justifies everything. Fear makes it okay to have surrendered freedom after freedom, until our every move is tracked and recorded in a dozen databases the average man will never have access to. Fear creates, defines, and shapes our world, and without it, most of us would have no idea what to do with ourselves. Our ancestors dreamed of a world without boundaries, while we dream new boundaries to put around our homes, our children, and ourselves. We limit our potential day after day in the name of a safety that we refuse to ever achieve. We took a world that was huge with possibility, and we made it as small as we could. ~ Mira Grant
56:I’m probably the only sixteen-year-old girl in a three hundred mile radius who knows how to distinguish between a poltergeist from an actual ghost (hint: If you can disrupt it with nitric acid, or if it throws new crap at you every time, it’s a poltergeist), or how to tell if a medium’s real or faking it (poke ‘em with a true iron needle). I know the six signs of a good occult store (Number One is the proprietor bolts the door before talking about Real Business) and the four things you never do when you’re in a bar with other people who know about the darker side of the world (don’t look weak). I know how to access public information and talk my way around clerks in courthouses (a smile and the right clothing will work wonders). I also know how to hack into newspaper files, police reports, and some kinds of government databases (primary rule: Don’t get caught. Duh). ~ Lilith Saintcrow
57:Yes, but all that’s needed is to break reciprocity,” he answered. “By controlling information, making sure it flows one way. Take over the databases. Trump up panic situations, so the public will support paternalistic ‘protections.’ Make sure lots of privacy laws get passed, then bribe open some back doors, so elites can see it all anyway, and ‘privacy’ only protects them. “Of course there’s more to the program than that,” Hamish continued, gaining momentum. “The smarty-pants knowledge castes will see what’s happening and complain. So you propagandize a lot of populist resentment against the scientists and other professionals, calling them ‘smug elites.’ Finally … when the civil servants and techies have lost the public’s trust, just cut the other estates out of the information loop, take complete control over the cameras and government agencies and voilà! A tyranny that lasts millennia! ~ David Brin
58:I think the best life would be one that's lived off the grid. No bills, your name in no government databases. No real proof you're even who you say you are, aside from, you know, being who you say you are. I don't mean living in a mountain hut with solar power and drinking well water. I think nature's beautiful and all, but I don't have any desire to live in it. I need to live in a city. I need pay as you go cell phones in fake names, wireless access stolen or borrowed from coffee shops and people using old or no encryption on their home networks. Taking knife fighting classes on the weekend! Learning Cantonese and Hindi and how to pick locks. Getting all sorts of skills so that when your mind starts going, and you're a crazy raving bum, at least you're picking their pockets while raving in a foreign language at smug college kids on the street. At least you're always gonna be able to eat. ~ Joey Comeau
59:According to a recent report from the research firm Gartner Inc., “through 2017, 60% of big-data projects will fail to go beyond piloting and experimentation and will be abandoned.” It turns out that faith in Hadoop has outpaced the technology’s ability to bring big data into the mainstream. Demand for Hadoop is on the rise, yet customers have found that a technology built to index the Web may not be sufficient for corporate big-data tasks, said Nick Heudecker, research director for information management at Gartner. It can take a lot of work to combine data stored in legacy repositories with the data that’s stored in Hadoop. And while Hadoop can be much faster than traditional databases for some purposes, it often isn’t fast enough to respond to queries immediately or to work on incoming information in real time. Satisfying requirements for data security and governance also poses a challenge. ~ Anonymous
60:Symbolist machine learning is an offshoot of the knowledge engineering school of AI. In the 1970s, so-called knowledge-based systems scored some impressive successes, and in the 1980s they spread rapidly, but then they died out. The main reason they did was the infamous knowledge acquisition bottleneck: extracting knowledge from experts and encoding it as rules is just too difficult, labor-intensive, and failure-prone to be viable for most problems. Letting the computer automatically learn to, say, diagnose diseases by looking at databases of past patients’ symptoms and the corresponding outcomes turned out to be much easier than endlessly interviewing doctors. Suddenly, the work of pioneers like Ryszard Michalski, Tom Mitchell, and Ross Quinlan had a new relevance, and the field hasn’t stopped growing since. (Another important problem was that knowledge-based systems had trouble dealing with uncertainty, of which more in Chapter 6.) ~ Pedro Domingos
61:Integration databases—don’t do it! Seriously! Not even with views. Not even with stored procedures. Take it up a level, and wrap a web service around the database. Then make the web service redundant and accessed through a virtual IP. Build a test harness to verify what happens when the web service is down. That’s an enterprise integration technology. Reaching into another system’s database is just…icky. Nothing hobbles a system’s ability to adapt quite like having other systems poking into its guts. Database “integrations” are pure evil. They violate encapsulation and information hiding by exposing the most intimate details about a system’s inner workings. They encourage inappropriate coupling at both the structural and semantic levels. Even worse, the system that hangs its database out for the world cannot trust the data in the database at all. Rows can be added or modified by other entities even while the owner has objects in memory mapped from those rows. Vital application logic can be bypassed, resulting in illegal or unreachable states.[119] ~ Anonymous
62:Scrolling through the rest of the 3,500 documents in Michelle’s hard drive, one comes upon a file titled “RecentDNAresults,” which features the EAR’s Y-STR markers (short tandem repeats on the Y chromosome that establish male-line ancestry), including the elusive rare PGM marker. Having the Golden State Killer’s DNA was always the one ace up this investigation’s sleeve. But a killer’s DNA is only as good as the databases we can compare it to. There was no match in CODIS. And there was no match in the California penal system’s Y-STR database. If the killer’s father, brothers, or uncles had been convicted of a felony in the past sixteen years, an alert would have gone to Paul Holes or Erika Hutchcraft (the current lead investigator in Orange County). They would have looked into the man’s family, zeroed in on a member who was in the area of the crimes, and launched an investigation. But they had nothing. There are public databases that the DNA profile could be used to match, filled not with convicted criminals but with genealogical buffs. You can enter the STR markers on the Y chromosome of the killer into these public databases and try to find a match, or at least a surname that could help you with the search. ~ Michelle McNamara
63:Scrolling through the rest of the 3,500 documents in Michelle’s hard drive, one comes upon a file titled “RecentDNAresults,” which features the EAR’s Y-STR markers (short tandem repeats on the Y chromosome that establish male-line ancestry), including the elusive rare PGM marker. Having the Golden State Killer’s DNA was always the one ace up this investigation’s sleeve. But a killer���s DNA is only as good as the databases we can compare it to. There was no match in CODIS. And there was no match in the California penal system’s Y-STR database. If the killer’s father, brothers, or uncles had been convicted of a felony in the past sixteen years, an alert would have gone to Paul Holes or Erika Hutchcraft (the current lead investigator in Orange County). They would have looked into the man’s family, zeroed in on a member who was in the area of the crimes, and launched an investigation. But they had nothing. There are public databases that the DNA profile could be used to match, filled not with convicted criminals but with genealogical buffs. You can enter the STR markers on the Y chromosome of the killer into these public databases and try to find a match, or at least a surname that could help you with the search. ~ Michelle McNamara
64:Steps in the IPB Process  First, define the battlefield environment. Identify characteristics of the battlefield that influence both friendly and competitor operations. Establish the limits of the battlefield and identify elements that are unknown but should be known.  Second, describe the battlefield’s effects on operations. This step always includes an examination of terrain and weather but may also include the characteristics of geography and infrastructure and their effects on friendly and threat operations, as well as such factors as politics, civilian press, local population, and demographics.  The third step is to evaluate the competitor. If the competitor is known, determine how it normally organizes for combat and conducts operations under similar circumstances. This information can be drawn from historical databases and well-developed threat models. With new or less well-known competitors, intelligence databases and threat courses of action may have to be developed simultaneously.  Finally, determine the competitor’s possible courses of action. The main question to be answered here is: Given what the competitor normally prefers to do and the effects of the specific environment in which it is operating, what are its likely objectives and courses of action? ~ Anonymous
65:Livingston: What do you think makes a good hacker? Spolsky: I think what makes a good hack is the observation that you can do without something that everybody else thinks you need. To me, the most elegant hack is when somebody says, "These 2,000 lines of code end up doing the same thing as those 2 lines of code would do. I know it seems complicated, but arithmetically it's really the same." When someone cuts through a lot of crap and says, "You know, it doesn't really matter." For example, Ruby on Rails is a framework that you can use with the Ruby programming language to access databases. It is the first framework that you can use from any programming language for accessing databases to realize that it's OK to require that the names of the columns in the database have a specific format. Everybody else thought, "You need to be allowed to use whatever name you want in the database and whatever name you want in the application." Therefore you have to create all this code to map between the name in the database and the name in the application. Ruby on Rails finally said, "It's no big deal if you're just forced to use the same name in both places. You know, it doesn't really matter." And suddenly it becomes much simpler and much cleaner. To me, that is an elegant hack—saying, "This particular distinction that we used to fret over, just throw it away. ~ Jessica Livingston
66:The gathering of information to control people is fundamental to any ruling power. As resistance to land acquisition and the new economic policies spreads across India, in the shadow of outright war in Central India, as a containment technique, India’s government has embarked on a massive biometrics program, perhaps one of the most ambitious and expensive information gathering projects in the world—the Unique Identification Number (UID). People don’t have clean drinking water, or toilets, or food, or money, but they will have election cards and UID numbers. Is it a coincidence that the UID project run by Nandan Nilekani, former CEO of Infosys, ostensibly meant to “deliver services to the poor,” will inject massive amounts of money into a slightly beleaguered IT industry?50 To digitize a country with such a large population of the illegitimate and “illegible”—people who are for the most part slum dwellers, hawkers, Adivasis without land records—will criminalize them, turning them from illegitimate to illegal. The idea is to pull off a digital version of the Enclosure of the Commons and put huge powers into the hands of an increasingly hardening police state. Nilekani’s technocratic obsession with gathering data is consistent with Bill Gates’s obsession with digital databases, numerical targets, and “scorecards of progress” as though it were a lack of information that is the cause of world hunger, and not colonialism, debt, and skewed profit-oriented corporate policy.51 ~ Arundhati Roy
67:So for most of the late twentieth century, political scientists embraced blank-slate theories in which people soaked up the ideology of their parents or the TV programs they watched. Some political scientists even said that most people were so confused about political issues that they had no real ideology at all.
But then came the studies of twins. In the 1980s, when scientists began analyzing large databases that allowed them to compare identical twins (who share all of their genes, plus, usually, their prenatal and childhood environments) to same-sex fraternal twins (who share half of their genes, plus their prenatal and childhood environments), they found that the identical twins were more similar on just about everything. And what’s more, identical twins reared in separate households (because of adoption) usually turn out to be very similar, whereas unrelated children reared together (because of adoption) rarely turn out similar to each other, or to their adoptive parents; they tend to be more similar to their genetic parents. Genes contribute, somehow, to just about every aspect of our personalities.
We’re not just talking about IQ, mental illness, and basic personality traits such as shyness. We’re talking about the degree to which you like jazz, spicy foods, and abstract art; your likelihood of getting a divorce or dying in a car crash; your degree of religiosity, and your political orientation as an adult. Whether you end up on the right or the left of the political spectrum turns out to be just as heritable as most other traits: genetics explains between a third and a half of the variability among people on their political attitudes. Being raised in a liberal or conservative household accounts for much less. ~ Jonathan Haidt
68:The cornerstone of control is the state’s system of surveillance, exposed by Snowden. I saw the effect of blanket surveillance as a reporter in the Stasi sate of Communist East Germany. I was followed by men, invariably with crew cuts and leather jackets, whom I presumed to be agents of the Stasi— the Ministry for State Security, which the ruling Communist Party described as the “shield and sword” of the nation. Stasi agents visited those I interviewed soon after I left their homes. My phone was bugged. Some of those I worked with were pressured to become informants. Fear hung like icicles over every conversation. People would whisper to me to convey the most banal pieces of information.

The Stasi did not set up massive death camps and gulags. It did not have to. Its network of as many as 2 million informants in a country of 17 million was everywhere. There were 102,000 secret police officers employed full-time to monitor the population— one for every 166 East Germans. The Nazis broke bones. The Stasi broke souls. The East German security apparatus pioneered the psychological disintegration skills that torturers and interrogators in America’s black sites, and within our prison system, have honed to a chilling perfection.

The goal of wholesale surveillance, as Hannah Arendt wrote in The Origins of Totalitarianism, is not, in the end, to discover crimes, “but to be on hand when the government decides to arrest a certain category of the population”. This is what happened to [Lynne] Stewart. And because Americans’ emails, phone conversations, Web searches, and geographical movements are recorded and stored in perpetuity in government databases, there will be more than enough “evidence” to seize us should the state deem it necessary. This information waits like a dormant virus inside government vaults to be released against us. It does not matter how trivial or innocent that information is. In totalitarian states, justice, like truth, is irrelevant. ~ Chris Hedges
69:Guess you’re wondering why I wanted to see you,” the lieutenant said.
“A little, yeah.” Linc didn’t bother to ask how Warren had gotten his address.
“I realized last time we talked that I didn’t know your last name.”
“That would be because I never mentioned it.”
The other man chuckled. “Right. And I didn’t want to ask the Corellis. So, I, uh, ran your plates.”
That was why he’d walked them to the hospital parking lot.
“I was curious. No offense, but in this type of case you cover all your bases.”
Linc knew what was coming. He folded his arms over his chest, listening more to the birds in the willow tree than to the lieutenant.
“I got the basic screen. Full name, address, date of birth. You’re an organ donor. After that, nada. Level Five block. Access to subject information restricted.”
Linc sighed.
“That’s federal, isn’t it?” The lieutenant looked over at him. “But not the FBI. Those guys comb their hair. You with the agency? The army?”
“Want me to lie?”
“No, of course not.” Mike Warren seemed awfully pleased with himself. “I did get your last name. Nice to meet a real Bannon.”
Linc braced himself, prepared to field irrelevant questions about his brother RJ and the Montgomery case, but the lieutenant seemed inclined to stop while he was ahead.
“Look, I know your connection to Kenzie is personal. But that doesn’t mean you have nothing to contribute. Going forward, if you can help, it would be just between you and me. Totally off the record.”
Linc knew what Mike Warren was getting at. Different databases, different protocols. Not a lot of sharing. The lieutenant was way out of his league, but he had the guts to ask. Linc respected that.
“Happy to,” he replied. “But there are limits.”
“I understand.” Mike Warren got up and looked toward Linc’s car. “Okay. I have to get back to the station. I’ll let you get back to whatever you were doing.”
“Sorting socks.”
The lieutenant grinned. “My apologies for the interruption. ~ Janet Dailey
70:Give us an idea of…” Noya Baram rubs her temples. “Oh, well.” Augie begins to stroll around again. “The examples are limitless. Small examples: elevators stop working. Grocery-store scanners. Train and bus passes. Televisions. Phones. Radios. Traffic lights. Credit-card scanners. Home alarm systems. Laptop computers will lose all their software, all files, everything erased. Your computer will be nothing but a keyboard and a blank screen. “Electricity would be severely compromised. Which means refrigerators. In some cases, heat. Water—well, we have already seen the effect on water-purification plants. Clean water in America will quickly become a scarcity. “That means health problems on a massive scale. Who will care for the sick? Hospitals? Will they have the necessary resources to treat you? Surgical operations these days are highly computerized. And they will not have access to any of your prior medical records online. “For that matter, will they treat you at all? Do you have health insurance? Says who? A card in your pocket? They won’t be able to look you up and confirm it. Nor will they be able to seek reimbursement from the insurer. And even if they could get in contact with the insurance company, the insurance company won’t know whether you’re its customer. Does it have handwritten lists of its policyholders? No. It’s all on computers. Computers that have been erased. Will the hospitals work for free? “No websites, of course. No e-commerce. Conveyor belts. Sophisticated machinery inside manufacturing plants. Payroll records. “Planes will be grounded. Even trains may not operate in most places. Cars, at least any built since, oh, 2010 or so, will be affected. “Legal records. Welfare records. Law enforcement databases. The ability of local police to identify criminals, to coordinate with other states and the federal government through databases—no more. “Bank records. You think you have ten thousand dollars in your savings account? Fifty thousand dollars in a retirement account? You think you have a pension that allows you to receive a fixed payment every month?” He shakes his head. “Not if computer files and their backups are erased. Do banks have a large wad of cash, wrapped in a rubber band with your name on it, sitting in a vault somewhere? Of course not. It’s all data.” “Mother of God,” says Chancellor Richter, wiping his face with a handkerchief. ~ Bill Clinton
71:For almost all astronomical objects, gravitation dominates, and they have the same unexpected behavior. Gravitation reverses the usual relation between energy and temperature. In the domain of astronomy, when heat flows from hotter to cooler objects, the hot objects get hotter and the cool objects get cooler. As a result, temperature differences in the astronomical universe tend to increase rather than decrease as time goes on. There is no final state of uniform temperature, and there is no heat death. Gravitation gives us a universe hospitable to life. Information and order can continue to grow for billions of years in the future, as they have evidently grown in the past. The vision of the future as an infinite playground, with an unending sequence of mysteries to be understood by an unending sequence of players exploring an unending supply of information, is a glorious vision for scientists. Scientists find the vision attractive, since it gives them a purpose for their existence and an unending supply of jobs. The vision is less attractive to artists and writers and ordinary people. Ordinary people are more interested in friends and family than in science. Ordinary people may not welcome a future spent swimming in an unending flood of information. A darker view of the information-dominated universe was described in the famous story “The Library of Babel,” written by Jorge Luis Borges in 1941.§ Borges imagined his library, with an infinite array of books and shelves and mirrors, as a metaphor for the universe. Gleick’s book has an epilogue entitled “The Return of Meaning,” expressing the concerns of people who feel alienated from the prevailing scientific culture. The enormous success of information theory came from Shannon’s decision to separate information from meaning. His central dogma, “Meaning is irrelevant,” declared that information could be handled with greater freedom if it was treated as a mathematical abstraction independent of meaning. The consequence of this freedom is the flood of information in which we are drowning. The immense size of modern databases gives us a feeling of meaninglessness. Information in such quantities reminds us of Borges’s library extending infinitely in all directions. It is our task as humans to bring meaning back into this wasteland. As finite creatures who think and feel, we can create islands of meaning in the sea of information. Gleick ends his book with Borges’s image of the human condition: We walk the corridors, searching the shelves and rearranging them, looking for lines of meaning amid leagues of cacophony and incoherence, reading the history of the past and of the future, collecting our thoughts and collecting the thoughts of others, and every so often glimpsing mirrors, in which we may recognize creatures of the information. ~ Freeman Dyson
72:Here’s a simple definition of ideology: “A set of beliefs about the proper order of society and how it can be achieved.”8 And here’s the most basic of all ideological questions: Preserve the present order, or change it? At the French Assembly of 1789, the delegates who favored preservation sat on the right side of the chamber, while those who favored change sat on the left. The terms right and left have stood for conservatism and liberalism ever since. Political theorists since Marx had long assumed that people chose ideologies to further their self-interest. The rich and powerful want to preserve and conserve; the peasants and workers want to change things (or at least they would if their consciousness could be raised and they could see their self-interest properly, said the Marxists). But even though social class may once have been a good predictor of ideology, that link has been largely broken in modern times, when the rich go both ways (industrialists mostly right, tech billionaires mostly left) and so do the poor (rural poor mostly right, urban poor mostly left). And when political scientists looked into it, they found that self-interest does a remarkably poor job of predicting political attitudes.9 So for most of the late twentieth century, political scientists embraced blank-slate theories in which people soaked up the ideology of their parents or the TV programs they watched.10 Some political scientists even said that most people were so confused about political issues that they had no real ideology at all.11 But then came the studies of twins. In the 1980s, when scientists began analyzing large databases that allowed them to compare identical twins (who share all of their genes, plus, usually, their prenatal and childhood environments) to same-sex fraternal twins (who share half of their genes, plus their prenatal and childhood environments), they found that the identical twins were more similar on just about everything.12 And what’s more, identical twins reared in separate households (because of adoption) usually turn out to be very similar, whereas unrelated children reared together (because of adoption) rarely turn out similar to each other, or to their adoptive parents; they tend to be more similar to their genetic parents. Genes contribute, somehow, to just about every aspect of our personalities.13 We’re not just talking about IQ, mental illness, and basic personality traits such as shyness. We’re talking about the degree to which you like jazz, spicy foods, and abstract art; your likelihood of getting a divorce or dying in a car crash; your degree of religiosity, and your political orientation as an adult. Whether you end up on the right or the left of the political spectrum turns out to be just as heritable as most other traits: genetics explains between a third and a half of the variability among people on their political attitudes.14 Being raised in a liberal or conservative household accounts for much less. How can that be? How can there be a genetic basis for attitudes about nuclear power, progressive taxation, and foreign aid when these issues only emerged in the last century or two? And how can there be a genetic basis for ideology when people sometimes change their political parties as adults? To answer these questions it helps to return to the definition of innate that I gave in chapter 7. Innate does not mean unmalleable; it means organized in advance of experience. The genes guide the construction of the brain in the uterus, but that’s only the first draft, so to speak. The draft gets revised by childhood experiences. To understand the origins of ideology you have to take a developmental perspective, starting with the genes and ending with an adult voting for a particular candidate or joining a political protest. There are three major steps in the process. Step ~ Jonathan Haidt

IN CHAPTERS









WORDNET



--- Overview of noun database

The noun database has 1 sense (no senses from tagged texts)
                  
1. database ::: (an organized body of related information)




--- Synonyms/Hypernyms (Ordered by Estimated Frequency) of noun database

1 sense of database                          

Sense 1
database
   => information, info
     => message, content, subject matter, substance
       => communication
         => abstraction, abstract entity
           => entity




--- Hyponyms of noun database

1 sense of database                          

Sense 1
database
   => list, listing
   => electronic database, on-line database, computer database, electronic information service
   => subdata base




--- Synonyms/Hypernyms (Ordered by Estimated Frequency) of noun database

1 sense of database                          

Sense 1
database
   => information, info










--- Coordinate Terms (sisters) of noun database

1 sense of database                          

Sense 1
database
  -> information, info
   => ammunition
   => factoid
   => misinformation
   => material
   => details, inside information
   => fact
   => format, formatting, data format, data formatting
   => gen
   => database
   => news, intelligence, tidings, word
   => news
   => nuts and bolts
   => intelligence, intelligence information
   => confirmation
   => insider information
   => secret, arcanum
   => secret
   => propaganda
   => course of study, program, programme, curriculum, syllabus
   => news
   => evidence
   => readout, read-out
   => tabulation, tabular matter
   => skinny
   => stuff
   => report card, report










--- Grep of noun database
computer database
database
database management
database management system
electronic database
lexical database
object-oriented database
object-oriented database management system
on-line database
patent and trademark office database
relational database
relational database management system





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Psychology Wiki - Diseases_Database
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Wikipedia - Falcon (storage engine) -- Storage engine for the MySQL relational database management systems
Wikipedia - FARME -- biological database
Wikipedia - FDA Adverse Event Reporting System -- US FDA supporting computerized database
Wikipedia - Federated database system
Wikipedia - Federated database
Wikipedia - FileMaker -- Database management system
Wikipedia - Find a Grave -- online database of cemetery records
Wikipedia - Firebird (database server) -- Relational database management system
Wikipedia - Flat file database
Wikipedia - Flat-file database -- Database stored as an ordinary unstructured file
Wikipedia - Flora of North America -- Book, website, database
Wikipedia - FoundationDB -- Free and open-source multi-model NoSQL database developed by Apple
Wikipedia - Fourth normal form -- Normal form used in database normalization
Wikipedia - Frank Bisby -- Botanist and pioneer in developing taxonomy databases (1945-2011)
Wikipedia - Freebase (database) -- Online knowledge base (2007-2016)
Wikipedia - Freesound -- Collaborative database of audio snippets, samples, recordings, bleeps
Wikipedia - Frequent pattern discovery -- Technique for database mining
Wikipedia - Full-text database
Wikipedia - GC-Wiki -- British internal intelligence database
Wikipedia - Gemstone Database Management System
Wikipedia - Gemstone (database)
Wikipedia - GeneCards -- Human gene database maintained by the Weizmann Institute of Science
Wikipedia - Gene Disease Database
Wikipedia - Generic Model Organism Database
Wikipedia - Geographic Names Information System -- Geographical database
Wikipedia - GeoNames -- Geographical database available and accessible through various web services
Wikipedia - GEOnet Names Server -- Database of geographical objects maintained by the United States National Geospatial-Intelligence Agency
Wikipedia - Giphy -- American online database and search engine
Wikipedia - Glacio-geological databases -- Data on glacially associated sedimentary deposits and erosional activity from former and current ice-sheets
Wikipedia - Global Historical Climatology Network -- A database of temperature, precipitation and pressure records
Wikipedia - Global Terrorism Database -- Post-1970 terrorist incident database by the University of Maryland, College Park
Wikipedia - Glottolog -- Bibliographic database of the world's lesser-known languages, maintained at the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany.
Wikipedia - Google Tables -- Cloud-based collaborative database software
Wikipedia - Government database
Wikipedia - Grand Comics Database
Wikipedia - Graph databases
Wikipedia - Graph Database
Wikipedia - Graph database -- Database that uses mathematical graphs to store and search data
Wikipedia - Great Britain Historical GIS -- Database that documents and visualises the changing human geography of the British Isles
Wikipedia - GreeNC -- Wiki-database of plant lncRNAs
Wikipedia - Guide to Pharmacology -- pharmacology database
Wikipedia - GWAS catalog -- Online database of genome-wide association study results
Wikipedia - GWAS Central -- Genetic association study database
Wikipedia - Halloween Problem -- Phenomenon with database updates where a row is updated more than once
Wikipedia - HanCinema -- Korean film and drama database
Wikipedia - HeinOnline -- Online database for legal materials
Wikipedia - Heterogeneous database system
Wikipedia - Hierarchical database model
Wikipedia - Hierarchical database
Wikipedia - HOLMES 2 -- database of the United Kingdom government for major crimes
Wikipedia - HSQLDB -- Java-based database engine
Wikipedia - IBM Db2 Family -- Relational model database server
Wikipedia - IBM System R -- Relational database management system, first implementation of SQL
Wikipedia - ICANN -- American nonprofit organization that coordinates several Internet address databases
Wikipedia - ICWATCH -- Database of LinkedIn profiles hosted by WikilLeaks
Wikipedia - IEEE Xplore -- Research database focused on computer science, electrical engineering, electronics, and allied fields
Wikipedia - IMDb -- Online database for movies, television, and video games
Wikipedia - Index (database)
Wikipedia - Indexed Database API
Wikipedia - InfiniDB -- Database management software company based in Frisco, Texas
Wikipedia - Ingres (database)
Wikipedia - In-memory database
Wikipedia - InnoDB -- Storage engine for the MySQL database management system
Wikipedia - INTEGRALL -- biological database
Wikipedia - Intelligent database
Wikipedia - InterBase -- Relational database management system
Wikipedia - Interim Register of Marine and Nonmarine Genera -- Taxonomic database
Wikipedia - International Conference on Database Theory
Wikipedia - International Nucleotide Sequence Database Collaboration
Wikipedia - International Plant Names Index -- Database of plant names
Wikipedia - Internet Adult Film Database -- Online database of US pornographic films and actors
Wikipedia - Internet Broadway Database -- Online database of Broadway theatre productions and their personnel
Wikipedia - Internet Movie Database
Wikipedia - Internet Movie Firearms Database
Wikipedia - Internet Speculative Fiction Database
Wikipedia - IPUMS -- World's largest individual-level population database
Wikipedia - Irish Statute Book -- Irish legal website/database
Wikipedia - Isolation (database systems)
Wikipedia - Japanese Movie Database -- Online database of films and actors
Wikipedia - JASPAR -- Open-access database storing curated, non-redundant transcription factor (TF) binding profiles
Wikipedia - Java Database Connectivity
Wikipedia - Jewish Museum of the American West -- Online database of pioneer Jews of the western United States
Wikipedia - Jordan Antiquities Database and Information System -- Computer database of antiquities in Jordan
Wikipedia - Journal of Database Management
Wikipedia - JPL Small-Body Database -- Astronomy database
Wikipedia - Key-value database -- Data storage paradigm
Wikipedia - LacED -- biological database
Wikipedia - Legislation.gov.uk -- Official web-accessible database of the statute law of the United Kingdom
Wikipedia - Library of Latin Texts -- Database of Latin texts
Wikipedia - List of academic databases and search engines -- Wikipedia list article
Wikipedia - List of biodiversity databases -- Wikipedia list article
Wikipedia - List of biological databases
Wikipedia - List of databases using MVCC -- Wikipedia list article
Wikipedia - List of funding opportunity databases -- Wikipedia list article
Wikipedia - List of in-memory databases -- Wikipedia list article
Wikipedia - List of international databases on individual student achievement tests -- Wikipedia list article
Wikipedia - List of neuroscience databases -- Wikipedia list article
Wikipedia - List of online databases -- Wikipedia list article
Wikipedia - List of online music databases -- Wikimedia list article
Wikipedia - List of Prokaryotic names with Standing in Nomenclature -- Online database of prokaryotes taxonomy
Wikipedia - List of relational database management systems -- Wikipedia list article
Wikipedia - Lock (database)
Wikipedia - Logbook of The World -- Amateur radio verification database
Wikipedia - Logeion -- Database for Latin and Ancient Greek dictionaries
Wikipedia - Logical database design technique
Wikipedia - Lumiere (database) -- Database of European film box office admissions
Wikipedia - LyricWiki -- Former lyrics database
Wikipedia - Main memory database
Wikipedia - Management information base -- Database used for managing the entities in a communication network
Wikipedia - MariaDB -- Database management system, relational, open source, community developed fork of MySQL
Wikipedia - Mathematics Genealogy Project -- Web-based database for the academic genealogy of mathematicians
Wikipedia - M-CM-^Mslendingabok (genealogical database) -- Database of Icelandic genealogy
Wikipedia - MEGARes -- Curated antibiotic resistance gene database
Wikipedia - Memory (storage engine) -- Storage engine for the MySQL relational database management systems
Wikipedia - MICRO Relational Database Management System
Wikipedia - Microsoft Access -- Database manager that is part of the Microsoft Office package
Wikipedia - Microsoft Azure SQL Database
Wikipedia - Microsoft Cinemania -- Film database released annually by Microsoft between 1992 and 1997
Wikipedia - Microsoft Jet Database Engine
Wikipedia - Microsoft SQL Server -- Family of database software
Wikipedia - MINAS -- Database of Metal Ions in Nucleic AcidS
Wikipedia - Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer -- Medical database
Wikipedia - MNIST database
Wikipedia - Mobile database
Wikipedia - Model 204 -- Database management system for IBM mainframes
Wikipedia - MongoDB -- Cross-platform document-oriented database
Wikipedia - Motorcycle Hall of Fame -- American museum and database
Wikipedia - Mouse Genome Database
Wikipedia - MUBII-TB-DB -- biological database
Wikipedia - Multidimensional database
Wikipedia - Multimedia database
Wikipedia - Multi-model database -- Database management system
Wikipedia - Multiversion concurrency control -- Concurrency control method commonly used by database management systems
Wikipedia - MusicBrainz -- Online music metadata database
Wikipedia - MvirDB -- biological database
Wikipedia - MyAnimeList -- English-language anime and manga database website
Wikipedia - MySQL -- SQL database engine software
Wikipedia - National Center for Biotechnology Information -- Database branch of the US National Library of Medicine
Wikipedia - National Crime Information Center -- US central database of crime-related information
Wikipedia - National Database > Registration Authority
Wikipedia - National Do Not Call Registry -- Telephone database in the United States
Wikipedia - National Geoscience Database of Iran -- Iranian Geoscience government agency
Wikipedia - National Register Information System -- Database of properties that have been listed on the United States National Register of Historic Places
Wikipedia - National Register of Citizens for Assam -- Indian citizenship database originally by Assam state
Wikipedia - National Vulnerability Database
Wikipedia - Navigational Database
Wikipedia - Navigational database -- Database in which records or objects are found by following references from other objects
Wikipedia - Negative database
Wikipedia - Neo4j -- free and open-source graph database implemented in Java
Wikipedia - Neogene of the Old World -- Database related to natural history
Wikipedia - Network database model
Wikipedia - Network database
Wikipedia - NewsBank -- News database resource
Wikipedia - New South Wales Heritage Database -- Database maintained by the Office of Environment and Heritage (NSW, Australia)
Wikipedia - NewSQL -- Relational database management with a desiree scalable performance of NoSQL, by combining OLTP plus ACID schemes
Wikipedia - NGP VAN -- privately owned voter database and web hosting service provider
Wikipedia - NNDB -- Online biographical database
Wikipedia - Normattiva -- Italian law database
Wikipedia - NoSQL -- Database class for storage and retrieval of modeled data
Wikipedia - OBD Memorial -- Russian government database project
Wikipedia - Object-based spatial database
Wikipedia - ObjectDatabase++
Wikipedia - Object database -- Database management system
Wikipedia - ObjectDB -- Object database for Java
Wikipedia - Object-oriented database
Wikipedia - Object-relational database
Wikipedia - Online database
Wikipedia - On-Line Encyclopedia of Integer Sequences -- Online database of integer sequences
Wikipedia - OpenCorporates -- Database on corporate entities
Wikipedia - Open Database Connectivity -- ODBC, standard interface for accessing database systems
Wikipedia - Open Database License -- Share-alike license for databases
Wikipedia - OpenStreetMap -- Collaboratively edited world map available under free Open Database License
Wikipedia - Operational database
Wikipedia - Oracle database
Wikipedia - Oracle Database -- Proprietary database management system
Wikipedia - Oracle NoSQL Database
Wikipedia - Oracle Template Library -- C++ library for database access
Wikipedia - Oregon Performance Reporting Information System -- Database of workforce system in Oregon, USA
Wikipedia - Outline of databases
Wikipedia - Oxford English Corpus -- Is a text corpus and database of 21st century English
Wikipedia - Parallel database
Wikipedia - Partition (database)
Wikipedia - Persistence framework -- Database middleware
Wikipedia - Philosophy Research Index -- Indexing database
Wikipedia - PhpMyAdmin -- Database administration tool
Wikipedia - Physiotherapy Evidence Database -- Physical therapy-centered bibliographic database
Wikipedia - Placenames Database of Ireland -- Also known as logainm.ie,
Wikipedia - Plants of the World Online -- Online database of the world's plants
Wikipedia - Police National Computer -- UK database of criminal, driving and property records
Wikipedia - Postcode Address File -- British geographical database of all known Royal Mail postal addresses and postcodes
Wikipedia - Price of Weed -- User-generated price database for cannabis
Wikipedia - Probabilistic database
Wikipedia - Project MUSE -- Online database of journals and ebooks
Wikipedia - PROSPERO -- Online systematic review database
Wikipedia - Protein Data Bank -- International open access database of large biological molecules
Wikipedia - PubChem -- Chemical information database
Wikipedia - Query throughput -- Measurement of database system performance
Wikipedia - RAC: Repository of Antibiotic resistance Cassettes -- biological database
Wikipedia - Rate Your Music -- Online collaborative metadata database of music and film releases
Wikipedia - Rat Genome Database
Wikipedia - Reactome -- Database of biological pathways
Wikipedia - Realm (database)
Wikipedia - Real-time database
Wikipedia - REBASE (database) -- Database for DNA restriction enzymes
Wikipedia - Record (computer science) -- Information block that is part of a database (data row)
Wikipedia - Redis -- Open-source in-memory key-value database
Wikipedia - RefSeq -- Database containing reference sequences of genes, proteins and transcripts
Wikipedia - Registry of Toxic Effects of Chemical Substances -- Database of toxicity information
Wikipedia - Relational algebra -- Theory introduced for modeling relational databases
Wikipedia - Relational database management systems
Wikipedia - Relational database management system -- DBMS that is based on the relational model
Wikipedia - Relational databases
Wikipedia - Relational Database
Wikipedia - Relational database -- Digital database whose organization is based on the relational model of data
Wikipedia - Relational model -- Database model
Wikipedia - Relation (database)
Wikipedia - Remote Database Access -- Protocol standard for database access
Wikipedia - Research database
Wikipedia - Research Papers in Economics -- Bibliographic database for economics
Wikipedia - ResFinder -- biological database
Wikipedia - Roud Folk Song Index -- Database of English-language folksongs
Wikipedia - Row (database)
Wikipedia - Rundata -- Database of runic inscriptions
Wikipedia - Saccharomyces Genome Database
Wikipedia - Schema-agnostic databases
Wikipedia - ScienceDirect -- Website providing subscription-based access to a database of scientific and medical research
Wikipedia - Scopus -- Bibliographic database
Wikipedia - Security Account Manager -- Windows database that stores users' passwords
Wikipedia - Semantic data model -- Database model
Wikipedia - Sequence database
Wikipedia - SESAM (database)
Wikipedia - Sex offender registries in the United States -- Many sex offenders in the US must register themselves on a public US government database
Wikipedia - Shadow library -- Database of content that is a copy of content that is otherwise obscured or not accessible because of paywalls or other accessibility restrictions
Wikipedia - Shane's Chess Information Database
Wikipedia - Shard (database architecture) -- Horizontal partition of data in a database or search engine
Wikipedia - SIMBAD -- Astronomical database
Wikipedia - Simple Modular Architecture Research Tool -- Biological database
Wikipedia - Social Security Death Index -- Database of American death records
Wikipedia - Spanner (database)
Wikipedia - Spanner (distributed database technology)
Wikipedia - Sparksee (graph database) -- Graph database system
Wikipedia - Spatial database -- Database optimized for storing and querying data that represents objects defined in a geometric space
Wikipedia - Spatiotemporal database -- Database managing time and space information
Wikipedia - Species 2000 -- Federated taxonomic database system for species checklists
Wikipedia - SQLBuddy -- Database administration tool
Wikipedia - SQLite -- Serverless relational database management system (RDBMS)
Wikipedia - SQL Server Express -- Relational database management system
Wikipedia - Swiss Media Database -- TV program
Wikipedia - Symposium on Principles of Database Systems
Wikipedia - Table (database)
Wikipedia - Taxonomic database
Wikipedia - Template talk:Database models
Wikipedia - Template talk:Database-software-stub
Wikipedia - Template talk:Databases
Wikipedia - Template talk:Database
Wikipedia - Temporal database -- Database that stores information relating to past, present and future time
Wikipedia - Terminology-oriented database
Wikipedia - TerminusDB -- free and open-source graph database
Wikipedia - Terrorist Identities Datamart Environment -- U.S. government database
Wikipedia - The Cancer Imaging Archive (TCIA) -- Database of medical images for cancer research
Wikipedia - The Himalayan Database -- Elizabeth Hawley's climbing statistics
Wikipedia - The Political Graveyard -- Online database of American political figures
Wikipedia - Thermodynamic databases for pure substances -- Thermodynamic properties list
Wikipedia - TiDB -- NewSQL relational distributed database
Wikipedia - Time series database -- Unordered set of n-time-series possibly of different lengths
Wikipedia - Torah database -- Electronic collection of classic Jewish texts
Wikipedia - Transaction (database)
Wikipedia - Transaction log -- History of actions executed by a database management system
Wikipedia - Transport Research International Documentation -- US transportation research database
Wikipedia - Trigger (database)
Wikipedia - Trove -- Australian online library database aggregator
Wikipedia - Tz database -- Collaborative compilation of information about the world's time zones
Wikipedia - U-CARE -- biological database
Wikipedia - UniProt -- Database of protein sequences and functional information
Wikipedia - Unisys DMSII -- Database management system
Wikipedia - United Kingdom National DNA Database -- UK database of DNA records, established in 1995
Wikipedia - Versant Object Database
Wikipedia - Very large database
Wikipedia - VFDB -- biological database
Wikipedia - View (database)
Wikipedia - Virtual biobank -- Online database providing biobank data
Wikipedia - Voyages: The Trans-Atlantic Slave Trade Database -- Database at Emory University
Wikipedia - Vulnerability database -- Computer security vulnerabilities
Wikipedia - Web SQL Database
Wikipedia - Wikidata -- collaboratively edited and free multilingual knowledge database and graph hosted by the Wikimedia Foundation
Wikipedia - Wikipedia:Database download -- Information on downloading dumps of the wiki database
Wikipedia - Wikipedia:Database reports/User preferences -- Statistics on the user preferences of a wiki
Wikipedia - Wikipedia:Database reports -- Reports made by querying the wiki database
Wikipedia - WikiScanner -- Defunct database linking Wikipedia edits to institutions
Wikipedia - Windows Internal Database
Wikipedia - Women Also Know Stuff -- Database of women in political science
Wikipedia - World Atlas of Language Structures -- Database of the structures of many languages.
Wikipedia - World Database of Happiness -- Archive of research findings on subjective appreciation of life.
Wikipedia - World Ocean Database Project -- An international collection of ocean profile-plankton data
Wikipedia - World Register of Marine Species -- Web-based database of marine species
Wikipedia - World Spider Catalog -- Online taxonomic database
Wikipedia - XML databases
Wikipedia - XML database
Wikipedia - YAGO (database)
Wikipedia - Yago (database)
Wikipedia - Z39.50 -- Application layer communications protocol for searching and retrieving information from a database over a TCP/IP computer network
Wikipedia - Zope Object Database
Day Of The Warrior(1996) - The Legion to Ensure Total Harmony and Law (L.E.T.H.A.L.), is tracking a criminal mastermind known only as The Warrior. While investigating his combination diamond smuggling/art theft/porn production industry, the agents discover that he has cracked their secret database and has stolen the files on...
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Baldr Force Exe Resolution -- -- Satelight -- 4 eps -- Visual novel -- Action Drama Mecha Sci-Fi -- Baldr Force Exe Resolution Baldr Force Exe Resolution -- Any network runs all over the world, and the development of the information network reaches its acme. In this age, there are two developed worlds; "the real world" and "wired", or the virtual network world. -- -- Soma Toru belongs to a hacking group, Steppen Wolf, which runs around the network world freely. They attack the database of the UN forces as their last work. During this attack, he loses Nonomura Yuya, his friend as well as the team leader. Toru is arrested by the army. In exchange for letting him free, he has to work for an anti-hacker organization, the first squad of the UN Security Force Information Administration Bureau. -- -- Working for them, he is looking for the person who killed his friend, while the other members also have their own reason to fight. -- -- The three-way fights of the terrorist group, the security enterprise, and the army, continue every day. The various events occurred during the fight seem to be independent of each other at the first glance, but they're converging on one event as if they were attracted by something. -- -- Based on the game by GIGA. -- -- (Source: ANN) -- -- Licensor: -- Funimation -- OVA - Nov 10, 2006 -- 15,668 6.46
Eve no Jikan (Movie) -- -- Studio Rikka -- 1 ep -- Original -- Sci-Fi Slice of Life -- Eve no Jikan (Movie) Eve no Jikan (Movie) -- In the Japan of the future, employing androids for various purposes is nothing out of the ordinary. However, treating androids on the same level as humans is frowned upon, and there is constant paranoia surrounding the possibility of robots defying humans, their masters. Those who appear too trustworthy of their androids are chided and labeled "dori-kei," or "android-holics." -- -- High school student Rikuo Sakisaka notices when his house droid, Sammy, starts behaving curiously—she has been leaving the house without his instruction. When he inspects the movement logs in her database, a cryptic line grabs his attention: "Are you enjoying the time of EVE?" Accompanied by his friend Masakazu Masaki, Rikuo tracks the whereabouts of his houseroid to a cafe called Time of Eve, where it is forbidden for customers to display prejudice against one another. The cafe, Rikuo realizes, is frequented by both man and machine, with no evidence to tell either apart. -- -- Each customer—from the cheerful Akiko, to a robot dangerously close to breaking down—has their own story and challenges to overcome. While Rikuo tries to reveal Sammy's intentions, he begins to question the legitimacy of the fear that drives humans to regard androids as nothing more than mere tools. -- -- -- Licensor: -- NYAV Post, Pied Piper -- Movie - Mar 6, 2010 -- 108,248 8.04
Eve no Jikan (Movie) -- -- Studio Rikka -- 1 ep -- Original -- Sci-Fi Slice of Life -- Eve no Jikan (Movie) Eve no Jikan (Movie) -- In the Japan of the future, employing androids for various purposes is nothing out of the ordinary. However, treating androids on the same level as humans is frowned upon, and there is constant paranoia surrounding the possibility of robots defying humans, their masters. Those who appear too trustworthy of their androids are chided and labeled "dori-kei," or "android-holics." -- -- High school student Rikuo Sakisaka notices when his house droid, Sammy, starts behaving curiously—she has been leaving the house without his instruction. When he inspects the movement logs in her database, a cryptic line grabs his attention: "Are you enjoying the time of EVE?" Accompanied by his friend Masakazu Masaki, Rikuo tracks the whereabouts of his houseroid to a cafe called Time of Eve, where it is forbidden for customers to display prejudice against one another. The cafe, Rikuo realizes, is frequented by both man and machine, with no evidence to tell either apart. -- -- Each customer—from the cheerful Akiko, to a robot dangerously close to breaking down—has their own story and challenges to overcome. While Rikuo tries to reveal Sammy's intentions, he begins to question the legitimacy of the fear that drives humans to regard androids as nothing more than mere tools. -- -- Movie - Mar 6, 2010 -- 108,248 8.04
Kyojinzoku no Hanayome -- -- Studio Hokiboshi -- 9 eps -- Manga -- Fantasy Shounen Ai -- Kyojinzoku no Hanayome Kyojinzoku no Hanayome -- Kouichi Mizuki ends his high school basketball career on a high note, bringing his team to victory during their final match at nationals. Now free from club activities, he looks forward to spending more time socializing, maybe even finding room for romance. But fate has slightly different plans for him when a magical circle transports Kouichi to Tildant, the land of giants. -- -- Upon his arrival, Kouichi comes face-to-face with Caius Lao Bistail, the titan king and the culprit behind his summoning. Caius is overjoyed, claiming Kouichi to be his fated bride and asking him to bear his children! It soon becomes evident to Kouichi that his species, let alone gender, is not a problem as Caius pushes him down onto a lavish bed. Will Kouichi ever find romance in this relationship that is bound to end in tears? -- -- -- -- The complete edition with explicit scenes was distributed online via Comic Festa Anime Zone. The censored version was broadcast on Tokyo MX. This database entry reflects censored TV version of the anime. -- 19,067 5.26
Robotics;Notes -- -- Production I.G -- 22 eps -- Visual novel -- Sci-Fi Mystery Drama Mecha School -- Robotics;Notes Robotics;Notes -- It has always been the aspiration of the Central Tanegashima High School Robotics Research Club to complete the GunPro1, a fully functioning giant robot. For years, the members of the club have contributed to its progress and it is now Akiho Senomiya's goal to finally make the dream of all the past club members become a reality. However, things are not as easy as they seem as the club lacks the funding for such a huge endeavor. Aside from that, the only other club member, Kaito Yashio, shows no interest in assisting his childhood friend and instead indulges in playing mecha-fighting games on his "PokeCom." -- -- As Kaito is in the middle of wasting his days, he receives an indecipherable message and hears a voice that seems to be drowned out by the noise of static. He searches for the source, only to realize that it came from Airi Yukifune, an AI which only exists within the augmented reality system accessible via the PokeCom. Robotic;Notes follows the story of Kaito as he discovers a peculiar report in Airi's database, one that would have disastrous consequences in the future. -- -- -- Licensor: -- Funimation -- 159,591 7.34
Shingeki no Kyojin: The Final Season Part 2 -- -- - -- ? eps -- Manga -- Action Military Mystery Super Power Drama Fantasy Shounen -- Shingeki no Kyojin: The Final Season Part 2 Shingeki no Kyojin: The Final Season Part 2 -- Second part of Shingeki no Kyojin: The Final Season. -- TV - Jan ??, 2022 -- 161,248 N/A -- -- Robotics;Notes -- -- Production I.G -- 22 eps -- Visual novel -- Sci-Fi Mystery Drama Mecha School -- Robotics;Notes Robotics;Notes -- It has always been the aspiration of the Central Tanegashima High School Robotics Research Club to complete the GunPro1, a fully functioning giant robot. For years, the members of the club have contributed to its progress and it is now Akiho Senomiya's goal to finally make the dream of all the past club members become a reality. However, things are not as easy as they seem as the club lacks the funding for such a huge endeavor. Aside from that, the only other club member, Kaito Yashio, shows no interest in assisting his childhood friend and instead indulges in playing mecha-fighting games on his "PokeCom." -- -- As Kaito is in the middle of wasting his days, he receives an indecipherable message and hears a voice that seems to be drowned out by the noise of static. He searches for the source, only to realize that it came from Airi Yukifune, an AI which only exists within the augmented reality system accessible via the PokeCom. Robotic;Notes follows the story of Kaito as he discovers a peculiar report in Airi's database, one that would have disastrous consequences in the future. -- -- -- Licensor: -- Funimation -- 159,591 7.34
https://wiki.archlinux.org/index.php/Category:Database_management_systems
https://wiki.archlinux.org/index.php/DeveloperWiki:UID_/_GID_Database
https://wiki.archlinux.org/index.php/List_of_applications#Database_tools
https://wiki.archlinux.org/index.php/List_of_applications/Documents#Database_tools
https://wiki.archlinux.org/index.php/List_of_applications#Simplified_database_software
https://wiki.archlinux.org/index.php/Open_Database_Connectivity
https://wiki.archlinux.org/index.php/Oracle_Database
https://wiki.archlinux.org/index.php/Oracle_Database_client
https://commons.wikimedia.org/wiki/Category:Images_from_Saga_Prefectural_Library_Database
https://commons.wikimedia.org/wiki/Category:Literature_databases
https://commons.wikimedia.org/wiki/Category:Music_databases
https://commons.wikimedia.org/wiki/Commons:Database_download
https://commons.wikimedia.org/wiki/Commons:Database_reports/Self-categorized_categories
https://commons.wikimedia.org/wiki/File:201603_database.png
https://commons.wikimedia.org/wiki/File:CPT-Databases-ExampleLinkTables.svg
ACM Transactions on Database Systems
Active database
Adult Film Database
Aerodrome mapping database
Aerospike (database)
Aid Worker Security Database
Alternative Splicing and Transcript Diversity database
Amazon Relational Database Service
Antimicrobial Drug Database
Aquatic toxicology databases
Arachne (archaeological database)
Asia-Pacific Trade Agreements Database
Atla Religion Database
Atmospheric chemistry observational databases
Atomicity (database systems)
Australasian Underwater Cultural Heritage Database
Australian Heritage Database
Australian National Bibliographic Database
Australian Rock Database
Back-end database
Beach Volleyball Database
Beilstein database
Bento (database)
Beta-Lactamase Database
Beta-Lactamase Database (BLAD)
Beta-Lactamase Database (BLDB)
BFI Film & TV Database
Bibliographic database
BioCyc database collection
Biological database
Biometric Database Law
Blockchain-based database
Book:Databases
Borland Database Engine
Building Performance Database
CAB Direct (database)
Calypso Ichthyological Database
Cambridge Structural Database
CAMPUS (database)
Canmore (database)
Carbohydrate Structure Database
CATH database
Centralized database
Chemical database
Chemical Database Service
Chess database
China Biographical Database
China Economic Databases
Chinese National Vulnerability Database
Christian Film Database
Circumpolar Health Bibliographic Database
Civil Engineering Database
Clara database
Clergy of the Church of England database
Cloud database
Column (database)
Comparison of database access
Comparison of database tools
Comparison of multi-model databases
Comparison of MySQL database engines
Comparison of object database management systems
Comparison of objectrelational database management systems
Comparison of relational database management systems
Comprehensive Antibiotic Resistance Database
Configuration management database
Conserved Domain Database
Consistency (database systems)
Controversial Ohio database searches of Joe Wurzelbacher
COSMIC cancer database
Cost database
Cross-strait language database
Crystallographic database
Crystallography Open Database
CSA (database company)
Cursor (databases)
Danish Film Database
Database
Database abstraction layer
Database administration
Database administrator
Database and Collections of Information Misappropriation Act
Database application
Database caching
Database Center for Life Science
Database-centric architecture
Database connection
Database design
Database Directive
Database dump
Database encryption
Database engine
Database forensics
Database index
Database (journal)
Database journalism
Database machine
Database Management Library
Database model
Database normalization
Database of Interacting Proteins
Database of Molecular Motions
Database of Salon Artists
Database preservation
Database publishing
Database right
Database schema
Database server
Database Software
Database storage structures
Database System Concepts
Database testing
Database theory
Database transaction
Database trigger
Database virtualization
Database Workbench
Data Security Threats Database
Db2 Database
Dietary Supplements (database)
Diseases Database
Distributionalrelational database
DNA database
Document-oriented database
DOTO Database
Drizzle (database server)
Durability (database systems)
Earth Human STR Allele Frequencies Database
Embedded database
Emissions & Generation Resource Integrated Database
Empress Embedded Database
Energy Citations Database
Energy Science and Technology Database
Ensembl genome database project
Eukaryotic Pathogen Database
Eukaryotic Promoter Database
European Cultivated Potato Database
European Sleep Apnea Database
European Soil Database
Evolutionary database design
Facial expression databases
FAME (database)
Families of Structurally Similar Proteins database
Federated database system
Financial Instruments Reference Database System
Firebird (database server)
Flat-file database
Food and Agriculture Organization Corporate Statistical Database
Freebase (database)
Full-text database
Functional database model
Gemstone (database)
Gender, Institutions and Development Database
Generic Model Organism Database
Genomes OnLine Database
Genome Taxonomy Database
German Emigrants Database
Glacio-geological databases
Glass databases
Global Research Identifier Database
Global Species Database
Gmelin database
Government database
G protein-coupled receptors database
Grand Comics Database
Graph database
Guardian (database)
Hekaton (database)
Helix (database)
Henry A. Wallace Police Crime Public Database
Heterogeneous database system
Hierarchical database model
Histone Database
Historical Marker Database
Hong Kong Movie DataBase
Human Metabolome Database
Human Mortality Database
Human Protein Reference Database
IMAGE (database)
In-database processing
Indexed Database API
Indian Genetic Disease Database
Informit (database)
Ingres (database)
In-memory database
Inorganic Crystal Structure Database
Intelligent database
International Conference on Database Theory
International Nucleotide Sequence Database Collaboration
Internet Adult Film Database
Internet Movie Cars Database
Internet Movie Firearms Database
Internet Speculative Fiction Database
Internet Theatre Database
Iraqi Legal Database
slendingabk (genealogical database)
Isolation (database systems)
Japanese Movie Database
Java Database Connectivity
Journal of Database Management
JPL Small-Body Database
Kaii-Ykai Densh Database
Keyvalue database
Ki Database
Korean Movie Database
Leiden Open Variation Database
Leuven Database of Ancient Books
Lightning Memory-Mapped Database
Line information database
List of academic databases and search engines
List of biodiversity databases
List of biological databases
List of databases for oncogenomic research
List of Drosophila databases
List of funding opportunity databases
List of genealogy databases
List of in-memory databases
List of international databases on individual student achievement tests
List of long non-coding RNA databases
List of neuroscience databases
List of online music databases
List of relational database management systems
List of tz database time zones
Lists of database management systems
Lumiere (database)
Manifesto Project Database
Materials database
Media contacts database
Microarray databases
MICRO Relational Database Management System
Microsoft Azure SQL Database
Microsoft Jet Database Engine
Middle Eastern Geodatabase for Antiquities (MEGA)
Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer
MNIST database
Mobile database
Model organism database
Molecular Modeling Database
Mouse Models of Human Cancer database
Multilingual Multiscript Plant Name Database
Multi-Omics Profiling Expression Database
MusicDNA (database)
Music ownership databases
Mustard Database
Names Database
NAPP (database)
NASA/IPAC Extragalactic Database
NASA Star and Exoplanet Database
National Database & Registration Authority
National Forensic DNA Database of South Africa
National Hip Fracture Database
National Pupil Database
National Vulnerability Database
Navigational database
NCI-Nature Pathway Interaction Database
Nearby Stars Database
New Zealand Nationally Significant Collections and Databases
Nintendo Network Service Database
Non-native speech database
Nuclear magnetic resonance database method
Nuclear magnetic resonance spectra database
Object database
Objectrelational database
Online database
Open Database Connectivity
Open Database License
Open energy system databases
Open Regulatory Annotation Database
Open Source Vulnerability Database
Operational database
Operon database
Oracle Database
Orientations of Proteins in Membranes database
Outline of databases
Pakistan MNP Database
Paleobiology Database
Paradox (database)
Parallel database
Partition (database)
PASCAL (database)
PDBbind database
Petrological Database of the Ocean Floor
Placenames Database of Ireland
Plant Proteome Database
Political Database of the Americas
Portable Database Image
Postcode Plants Database
Probabilistic database
Project-Level Aid Database
Protein database
Protein structure database
Proteomics Identifications Database
Raima Database Manager
Range query (database)
Rat Genome Database
Real-time database
Real-time Neutron Monitor Database
REBASE (database)
Relational database
Relation (database)
Remote Database Access
Reptile Database
Resistance Database Initiative
Riken integrated database of mammals
RNA modification database
Roller Coaster DataBase
Routing Assets Database
Row (database)
SARG database
Schema-agnostic databases
Scottish Built Ships database
Scylla (database)
Sequence database
SESAM (database)
Shane's Chess Information Database
Shard (database architecture)
SILVA ribosomal RNA database
Simple Sloppy Semantic Database
SIPRI Arms Transfers Database, Iraq 19731990
Small Molecule Pathway Database
Source Code in Database
Spanner (database)
Sparksee (graph database)
Spatial database
Spatiotemporal database
Spectral Database for Organic Compounds
SPIN bibliographic database
Structural Classification of Proteins database
Stuttgart Database of Scientific Illustrators 14501950
Suicide Attack Database
Superbase (database)
Superfamily database
Swedish Film Database
Symposium on Principles of Database Systems
Table (database)
TALON (database)
Tandem Repeats Database
Taxonomic database
Temporal database
Tephritid Workers Database
Terrorist Screening Database
Tethys (database)
The Big Cartoon DataBase
The Human-Induced Earthquake Database
Thermodynamic databases for pure substances
Threat Matrix (database)
Time series database
Torah database
Toxin and Toxin-Target Database
Transactional database
Transporter Classification Database
TV White Space Database
Tz database
UCLA Phonological Segment Inventory Database
United Kingdom National DNA Database
United Nations Multilingual Terminology Database
Upsizing (database)
Versant Object Database
VINITI Database RAS
Voter database
Vulnerability database
Web SQL Database
Windows Internal Database
World Database of Happiness
World Database on Protected Areas
World Inequality Database
XML database
YAGO (database)
Y Chromosome Haplotype Reference Database
Yeast Metabolome Database
Zope Object Database


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