Databases in the United Kingdom
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In
computing Computing is any goal-oriented activity requiring, benefiting from, or creating computing machinery. It includes the study and experimentation of algorithmic processes and development of both computer hardware , hardware and software. It has sci ...

computing
, a database is an organized collection of
data Data (; ) are individual facts A fact is something that is truth, true. The usual test for a statement of fact is verifiability—that is whether it can be demonstrated to correspond to experience. Standard reference works are often used ...
stored and accessed electronically from a
computer system A computer is a machine that can be programmed to Execution (computing), carry out sequences of arithmetic or logical operations automatically. Modern computers can perform generic sets of operations known as Computer program, programs. These ...
. Where databases are more complex they are often developed using formal design and modeling techniques. The
database management system In computing Computing is any goal-oriented activity requiring, benefiting from, or creating computing machinery. It includes the study and experimentation of algorithmic processes and development of both computer hardware , hardware and sof ...
(DBMS) is the
software Software is a collection of instructions Instruction or instructions may refer to: Computing * Instruction, one operation of a processor within a computer architecture instruction set * Computer program, a collection of instructions Music * I ...

software
that interacts with
end user In product development, an end user (sometimes end-user) is a person who ultimately uses or is intended to ultimately use a product. The end user stands in contrast to users who support or maintain the product, such as sysop A sysop (; an abbre ...
s, applications, and the database itself to capture and analyze the data. The DBMS software additionally encompasses the core facilities provided to administer the database. The sum total of the database, the DBMS and the associated applications can be referred to as a "database system". Often the term "database" is also used loosely to refer to any of the DBMS, the database system or an application associated with the database. Computer scientists may classify database-management systems according to the
database model A database model is a type of data model A data model (or datamodel) is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities. For instance, a data model may ...
s that they support.
Relational database A relational database is a digital database In , a database is an organized collection of stored and accessed electronically from a . Where databases are more complex they are often developed using formal techniques. The (DBMS) is the tha ...
s became dominant in the 1980s. These model data as rows and
columns A column or pillar in architecture upright=1.45, alt=Plan d'exécution du second étage de l'hôtel de Brionne (dessin) De Cotte 2503c – Gallica 2011 (adjusted), Plan of the second floor (attic storey) of the Hôtel de Brionne in Par ...
in a series of
tables Table may refer to: * Table (information) A table is an arrangement of information or data, typically in rows and columns, or possibly in a more complex structure. Tables are widely used in communication, research, and data analysis. Tables ap ...
, and the vast majority use
SQL SQL ( ''S-Q-L'', "sequel"; Structured Query Language) is a domain-specific languageA domain-specific language (DSL) is a computer languageA computer language is a method of communication with a computer A computer is a machine that can b ...

SQL
for writing and querying data. In the 2000s, non-relational databases became popular, referred to as
NoSQL A NoSQL (originally referring to "non-SQL SQL ( ''S-Q-L'', "sequel"; Structured Query Language) is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or fo ...
because they use different
query language In general, a query is a form of question A question is an utterance which typically functions as a request for information, which is expected to be provided in the form of an answer. Questions can thus be understood as a kind of illocutionary ...
s.


Terminology and overview

Formally, a "database" refers to a set of related data and the way it is organized. Access to this data is usually provided by a "database management system" (DBMS) consisting of an integrated set of computer software that allows
users User may refer to: Ancient Egyptian roles * User (ancient Egyptian official), an ancient Egyptian nomarch (governor) of the Eighth Dynasty * Useramen, an ancient Egyptian vizier also called "User" Other uses * User (computing), a person (or s ...
to interact with one or more databases and provides access to all of the data contained in the database (although restrictions may exist that limit access to particular data). The DBMS provides various functions that allow entry, storage and retrieval of large quantities of information and provides ways to manage how that information is organized. Because of the close relationship between them, the term "database" is often used casually to refer to both a database and the DBMS used to manipulate it. Outside the world of professional information technology, the term ''database'' is often used to refer to any collection of related data (such as a
spreadsheet A spreadsheet is a computer application for organization, analysis, and storage of data in table (information), tabular form. Spreadsheets were developed as computerized analogs of paper accounting Worksheet#Accounting, worksheets. The program op ...

spreadsheet
or a card index) as size and usage requirements typically necessitate use of a database management system. Existing DBMSs provide various functions that allow management of a database and its data which can be classified into four main functional groups: * Data definition – Creation, modification and removal of definitions that define the organization of the data. * Update – Insertion, modification, and deletion of the actual data. * Retrieval – Providing information in a form directly usable or for further processing by other applications. The retrieved data may be made available in a form basically the same as it is stored in the database or in a new form obtained by altering or combining existing data from the database. * Administration – Registering and monitoring users, enforcing data security, monitoring performance, maintaining data integrity, dealing with concurrency control, and recovering information that has been corrupted by some event such as an unexpected system failure. Both a database and its DBMS conform to the principles of a particular
database model A database model is a type of data model A data model (or datamodel) is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities. For instance, a data model may ...
. "Database system" refers collectively to the database model, database management system, and database. Physically, database servers are dedicated computers that hold the actual databases and run only the DBMS and related software. Database servers are usually
multiprocessor Multiprocessing is the use of two or more central processing units A central processing unit (CPU), also called a central processor, main processor or just Processor (computing), processor, is the electronic circuitry that executes Instruct ...
computers, with generous memory and
RAID Raid or RAID may refer to: Attack * Raid (military) Raiding, also known as depredation, is a military tactics, military tactic or operational warfare mission which has a specific purpose. Raiders do not capture and hold a location, but quickly ...
disk arrays used for stable storage. Hardware database accelerators, connected to one or more servers via a high-speed channel, are also used in large volume transaction processing environments. DBMSs are found at the heart of most
database application A database application is a computer program whose primary purpose is retrieving information from a computerized database. From here, information can be inserted, modified or deleted which is subsequently conveyed back into the database. Early exam ...
s. DBMSs may be built around a custom multitasking
kernel Kernel may refer to: Computing * Kernel (operating system), the central component of most operating systems * Kernel (image processing), a matrix used for image convolution * Compute kernel, in GPGPU programming * Kernel method, in machine learnin ...
with built-in networking support, but modern DBMSs typically rely on a standard
operating system An operating system (OS) is system software System software is software designed to provide a platform for other software. Examples of system software include operating systems (OS) like macOS, Linux, Android (operating system), Android and Mi ...

operating system
to provide these functions. Since DBMSs comprise a significant
market Market may refer to: *Market (economics) *Market economy *Marketplace, a physical marketplace or public market Geography *Märket, an island shared by Finland and Sweden Art, entertainment, and media Films *Market (1965 film), ''Market'' (1965 ...
, computer and storage vendors often take into account DBMS requirements in their own development plans. Databases and DBMSs can be categorized according to the database model(s) that they support (such as relational or XML), the type(s) of computer they run on (from a server cluster to a mobile phone), the
query language In general, a query is a form of question A question is an utterance which typically functions as a request for information, which is expected to be provided in the form of an answer. Questions can thus be understood as a kind of illocutionary ...
(s) used to access the database (such as SQL or
XQuery XQuery (XML Query) is a query and functional programming In computer science Computer science deals with the theoretical foundations of information, algorithms and the architectures of its computation as well as practical techniques ...
), and their internal engineering, which affects performance,
scalability Scalability is the property of a system to handle a growing amount of work by adding resources to the system. In an economic An economy (; ) is an area of the production Production may be: Economics and business * Production (economics ...
, resilience, and security.


History

The sizes, capabilities, and performance of databases and their respective DBMSs have grown in orders of magnitude. These performance increases were enabled by the technology progress in the areas of
processors A central processing unit (CPU), also called a central processor, main processor or just Processor (computing), processor, is the electronic circuitry that executes Instruction (computing), instructions comprising a computer program. The CPU per ...

processors
,
computer memory In computing Computing is any goal-oriented activity requiring, benefiting from, or creating computing machinery. It includes the study and experimentation of algorithmic processes and development of both computer hardware , hardware and soft ...
,
computer storage Computer data storage is a technology consisting of computer components and Data storage device, recording media that are used to retain digital data (computing), data. It is a core function and fundamental component of computers. The cent ...
, and
computer network A computer network is a set of computer A computer is a machine that can be programmed to Execution (computing), carry out sequences of arithmetic or logical operations automatically. Modern computers can perform generic sets of operati ...
s. The concept of a database was made possible by the emergence of direct access storage media such as magnetic disks, which became widely available in the mid 1960s; earlier systems relied on sequential storage of data on magnetic tape. The subsequent development of database technology can be divided into three eras based on data model or structure: navigational, SQL/ relational, and post-relational. The two main early navigational data models were the
hierarchical model A hierarchical database model is a data model A data model (or datamodel) is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities. For instance, a data model ...
and the
CODASYL CODASYL, the Conference/Committee on Data Systems Languages, was a consortium A consortium (plural: consortia) is an association Association may refer to: *Club (organization), an association of two or more people united by a common interest ...
model (
network model The network model is a database model A database model is a type of data model A data model (or datamodel) is an abstract model that organizes elements of data Data are units of information Information can be thought of as the reso ...
). These were characterized by the use of pointers (often physical disk addresses) to follow relationships from one record to another. The
relational model The relational model (RM) for database In computing, a database is an organized collection of Data (computing), data stored and accessed electronically from a computer system. Where databases are more complex they are often developed using form ...
, first proposed in 1970 by
Edgar F. Codd Edgar Frank "Ted" Codd (19 August 1923 – 18 April 2003) was an English computer scientist A computer scientist is a person who has acquired the knowledge of computer science Computer science deals with the theoretical foundations of ...
, departed from this tradition by insisting that applications should search for data by content, rather than by following links. The relational model employs sets of ledger-style tables, each used for a different type of entity. Only in the mid-1980s did computing hardware become powerful enough to allow the wide deployment of relational systems (DBMSs plus applications). By the early 1990s, however, relational systems dominated in all large-scale
data processing Data processing is, generally, "the collection Collection or Collections may refer to: * Cash collection, the function of an accounts receivable department * Collection agency, agency to collect cash * Collections management (museum) ** Colle ...

data processing
applications, and they remain dominant:
IBM DB2 Db2 is a family of data management products, including database servers, developed by IBM. They initially supported the relational model, but were extended to support object–relational features and non-relational structures like JSON and ...
,
Oracle An oracle is a person or agency Agency may refer to: * a governmental or other institution Institutions, according to Samuel P. Huntington, are "stable, valued, recurring patterns of behavior". Institutions can refer to mechanisms which go ...
,
MySQL MySQL () is an open-source Open source is source code that is made freely available for possible modification and redistribution. Products include permission to use the source code, design documents, or content of the product. The open-source m ...
, and
Microsoft SQL Server Microsoft SQL Server is a relational database management system A relational database is a digital database based on the relational model of data, as proposed by E. F. Codd in 1970. A system used to maintain relational databases is a relational ...
are the most searched
DBMS In computing Computing is any goal-oriented activity requiring, benefiting from, or creating computing machinery. It includes the study and experimentation of algorithmic processes and development of both computer hardware , hardware and sof ...

DBMS
. The dominant database language, standardised SQL for the relational model, has influenced database languages for other data models.
Object database An object database is a database management system In computing Computing is any goal-oriented activity requiring, benefiting from, or creating computing machinery. It includes the study and experimentation of algorithmic processes and de ...
s were developed in the 1980s to overcome the inconvenience of
object–relational impedance mismatch The object–relational impedance mismatch is a set of conceptual and technical difficulties that are often encountered when a relational database management system (RDBMS) is being served by an application program (or multiple application programs ...
, which led to the coining of the term "post-relational" and also the development of hybrid
object–relational database An object–relational database (ORD), or object–relational database management system (ORDBMS), is a database management system In computing Computing is any goal-oriented activity requiring, benefiting from, or creating computing machiner ...
s. The next generation of post-relational databases in the late 2000s became known as
NoSQL A NoSQL (originally referring to "non-SQL SQL ( ''S-Q-L'', "sequel"; Structured Query Language) is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or fo ...
databases, introducing fast key–value stores and
document-oriented database A document-oriented database, or document store, is a computer program In imperative programming, a computer program is a sequence of instructions in a programming language that a computer can execute or interpret. In declarative programming, ...
s. A competing "next generation" known as
NewSQL NewSQL is a class of relational database management system In computing Computing is any goal-oriented activity requiring, benefiting from, or creating computing machinery. It includes the study and experimentation of algorithmic processes an ...
databases attempted new implementations that retained the relational/SQL model while aiming to match the high performance of NoSQL compared to commercially available relational DBMSs.


1960s, navigational DBMS

The introduction of the term ''database'' coincided with the availability of direct-access storage (disks and drums) from the mid-1960s onwards. The term represented a contrast with the tape-based systems of the past, allowing shared interactive use rather than daily
batch processing Computerized batch processing is the running of "jobs that can run without end user interaction, or can be scheduled to run as resources permit." History The term "batch processing" originates in the traditional classification of methods of produc ...
. The
Oxford English Dictionary The ''Oxford English Dictionary'' (''OED'') is the principal historical dictionary A historical dictionary or dictionary on historical principles is a dictionary which deals not only with the latterday meanings of words but also the historica ...
cites a 1962 report by the System Development Corporation of California as the first to use the term "data-base" in a specific technical sense. As computers grew in speed and capability, a number of general-purpose database systems emerged; by the mid-1960s a number of such systems had come into commercial use. Interest in a standard began to grow, and
Charles Bachman Charles William Bachman III (December 11, 1924 – July 13, 2017) was an American computer scientist A computer scientist is a person who has acquired the knowledge of computer science, the study of the theoretical foundations of infor ...
, author of one such product, the
Integrated Data Store Integrated Data Store (IDS) was an early network database management system In computing Computing is any goal-oriented activity requiring, benefiting from, or creating computing machinery. It includes the study and experimentation of a ...
(IDS), founded the Database Task Group within
CODASYL CODASYL, the Conference/Committee on Data Systems Languages, was a consortium A consortium (plural: consortia) is an association Association may refer to: *Club (organization), an association of two or more people united by a common interest ...
, the group responsible for the creation and standardization of
COBOL COBOL (; an acronym An acronym is a word In linguistics, a word of a spoken language can be defined as the smallest sequence of phonemes that can be uttered in isolation with semantic, objective or pragmatics, practical meaning (lingui ...

COBOL
. In 1971, the Database Task Group delivered their standard, which generally became known as the ''CODASYL approach'', and soon a number of commercial products based on this approach entered the market. The CODASYL approach offered applications the ability to navigate around a linked data set which was formed into a large network. Applications could find records by one of three methods: #Use of a primary key (known as a CALC key, typically implemented by
hashing Hash, hashes, hash mark, or hashing may refer to: Substances * Hash (food) Hash is a culinary dish consisting of chopped meat, potatoes, and fried onions. The name is derived from , meaning "to chop". It originated as a way to use up leftov ...

hashing
) #Navigating relationships (called ''sets'') from one record to another #Scanning all the records in a sequential order Later systems added
B-tree In computer science Computer science deals with the theoretical foundations of information, algorithms and the architectures of its computation as well as practical techniques for their application. Computer science is the study of Algo ...

B-tree
s to provide alternate access paths. Many CODASYL databases also added a declarative query language for end users (as distinct from the navigational API). However CODASYL databases were complex and required significant training and effort to produce useful applications.
IBM International Business Machines Corporation (IBM) is an American multinational technology company headquartered in Armonk, New York, with operations in over 170 countries. The company began in 1911, founded in Endicott, New York, as the C ...
also had their own DBMS in 1966, known as
Information Management System The IBM Information Management System (IMS) is a joint hierarchical database A hierarchical database model is a data model A data model (or datamodel) is an abstract model that organizes elements of data Data are units of information I ...
(IMS). IMS was a development of software written for the
Apollo program The Apollo program, also known as Project Apollo, was the third United States human spaceflight program carried out by the NASA, National Aeronautics and Space Administration (NASA), which succeeded in Moon landing, landing the first humans ...

Apollo program
on the
System/360 The IBM System/360 (S/360) is a family of mainframe computer A mainframe computer, informally called a mainframe or big iron, is a computer used primarily by large organizations for critical applications like bulk data processing for t ...
. IMS was generally similar in concept to CODASYL, but used a strict hierarchy for its model of data navigation instead of CODASYL's network model. Both concepts later became known as navigational databases due to the way data was accessed: the term was popularized by Bachman's 1973
Turing Award The ACM A. M. Turing Award is an annual prize given by the Association for Computing Machinery The Association for Computing Machinery (ACM) is a US-based international for . It was founded in 1947 and is the world's largest scientific and e ...
presentation ''The Programmer as Navigator''. IMS is classified by IBM as a hierarchical database. IDMS and Cincom Systems' Cincom Systems#1970s, TOTAL database are classified as network databases. IMS remains in use .


1970s, relational DBMS

Edgar F. Codd Edgar Frank "Ted" Codd (19 August 1923 – 18 April 2003) was an English computer scientist A computer scientist is a person who has acquired the knowledge of computer science Computer science deals with the theoretical foundations of ...
worked at IBM in San Jose, California, in one of their offshoot offices that was primarily involved in the development of hard disk systems. He was unhappy with the navigational model of the CODASYL approach, notably the lack of a "search" facility. In 1970, he wrote a number of papers that outlined a new approach to database construction that eventually culminated in the groundbreaking ''A Relational Model of Data for Large Shared Data Banks''. In this paper, he described a new system for storing and working with large databases. Instead of records being stored in some sort of linked list of free-form records as in CODASYL, Codd's idea was to organize the data as a number of "
tables Table may refer to: * Table (information) A table is an arrangement of information or data, typically in rows and columns, or possibly in a more complex structure. Tables are widely used in communication, research, and data analysis. Tables ap ...
", each table being used for a different type of entity. Each table would contain a fixed number of columns containing the attributes of the entity. One or more columns of each table were designated as a primary key by which the rows of the table could be uniquely identified; cross-references between tables always used these primary keys, rather than disk addresses, and queries would join tables based on these key relationships, using a set of operations based on the mathematical system of relational calculus (from which the model takes its name). Splitting the data into a set of normalized tables (or ''relations'') aimed to ensure that each "fact" was only stored once, thus simplifying update operations. Virtual tables called ''views'' could present the data in different ways for different users, but views could not be directly updated. Codd used mathematical terms to define the model: relations, tuples, and domains rather than tables, rows, and columns. The terminology that is now familiar came from early implementations. Codd would later criticize the tendency for practical implementations to depart from the mathematical foundations on which the model was based. The use of primary keys (user-oriented identifiers) to represent cross-table relationships, rather than disk addresses, had two primary motivations. From an engineering perspective, it enabled tables to be relocated and resized without expensive database reorganization. But Codd was more interested in the difference in semantics: the use of explicit identifiers made it easier to define update operations with clean mathematical definitions, and it also enabled query operations to be defined in terms of the established discipline of first-order predicate calculus; because these operations have clean mathematical properties, it becomes possible to rewrite queries in provably correct ways, which is the basis of query optimization. There is no loss of expressiveness compared with the hierarchic or network models, though the connections between tables are no longer so explicit. In the hierarchic and network models, records were allowed to have a complex internal structure. For example, the salary history of an employee might be represented as a "repeating group" within the employee record. In the relational model, the process of normalization led to such internal structures being replaced by data held in multiple tables, connected only by logical keys. For instance, a common use of a database system is to track information about users, their name, login information, various addresses and phone numbers. In the navigational approach, all of this data would be placed in a single variable-length record. In the relational approach, the data would be ''normalized'' into a user table, an address table and a phone number table (for instance). Records would be created in these optional tables only if the address or phone numbers were actually provided. As well as identifying rows/records using logical identifiers rather than disk addresses, Codd changed the way in which applications assembled data from multiple records. Rather than requiring applications to gather data one record at a time by navigating the links, they would use a declarative query language that expressed what data was required, rather than the access path by which it should be found. Finding an efficient access path to the data became the responsibility of the database management system, rather than the application programmer. This process, called query optimization, depended on the fact that queries were expressed in terms of mathematical logic. Codd's paper was picked up by two people at Berkeley, Eugene Wong and Michael Stonebraker. They started a project known as INGRES using funding that had already been allocated for a geographical database project and student programmers to produce code. Beginning in 1973, INGRES delivered its first test products which were generally ready for widespread use in 1979. INGRES was similar to IBM System R, System R in a number of ways, including the use of a "language" for data access, known as QUEL query languages, QUEL. Over time, INGRES moved to the emerging SQL standard. IBM itself did one test implementation of the relational model, PRTV, and a production one, IBM Business System 12, Business System 12, both now discontinued. Honeywell wrote Multics Relational Data Store, MRDS for Multics, and now there are two new implementations: Dataphor, Alphora Dataphor and Rel (DBMS), Rel. Most other DBMS implementations usually called ''relational'' are actually SQL DBMSs. In 1970, the University of Michigan began development of the MICRO Relational Database Management System, MICRO Information Management System based on David L. Childs, D.L. Childs' Set-Theoretic Data model. MICRO was used to manage very large data sets by the US Department of Labor, the U.S. Environmental Protection Agency, and researchers from the University of Alberta, the University of Michigan, and Wayne State University. It ran on IBM mainframe computers using the Michigan Terminal System.''MICRO Information Management System (Version 5.0) Reference Manual''
M.A. Kahn, D.L. Rumelhart, and B.L. Bronson, October 1977, Institute of Labor and Industrial Relations (ILIR), University of Michigan and Wayne State University
The system remained in production until 1998.


Integrated approach

In the 1970s and 1980s, attempts were made to build database systems with integrated hardware and software. The underlying philosophy was that such integration would provide higher performance at a lower cost. Examples were IBM System/38, the early offering of Teradata, and the Britton Lee, Inc. database machine. Another approach to hardware support for database management was International Computers Limited, ICL's Content Addressable File Store, CAFS accelerator, a hardware disk controller with programmable search capabilities. In the long term, these efforts were generally unsuccessful because specialized database machines could not keep pace with the rapid development and progress of general-purpose computers. Thus most database systems nowadays are software systems running on general-purpose hardware, using general-purpose computer data storage. However, this idea is still pursued for certain applications by some companies like Netezza and Oracle (Exadata).


Late 1970s, SQL DBMS

IBM started working on a prototype system loosely based on Codd's concepts as ''IBM System R, System R'' in the early 1970s. The first version was ready in 1974/5, and work then started on multi-table systems in which the data could be split so that all of the data for a record (some of which is optional) did not have to be stored in a single large "chunk". Subsequent multi-user versions were tested by customers in 1978 and 1979, by which time a standardized
query language In general, a query is a form of question A question is an utterance which typically functions as a request for information, which is expected to be provided in the form of an answer. Questions can thus be understood as a kind of illocutionary ...
– SQL – had been added. Codd's ideas were establishing themselves as both workable and superior to CODASYL, pushing IBM to develop a true production version of System R, known as ''SQL/DS'', and, later, ''Database 2'' (IBM Db2 Family, DB2). Larry Ellison's Oracle Database (or more simply, Oracle_Database, Oracle) started from a different chain, based on IBM's papers on System R. Though Oracle V1 implementations were completed in 1978, it wasn't until Oracle Version 2 when Ellison beat IBM to market in 1979. Stonebraker went on to apply the lessons from INGRES to develop a new database, Postgres, which is now known as PostgreSQL. PostgreSQL is often used for global mission-critical applications (the .org and .info domain name registries use it as their primary data store, as do many large companies and financial institutions). In Sweden, Codd's paper was also read and Mimer SQL was developed from the mid-1970s at Uppsala University. In 1984, this project was consolidated into an independent enterprise. Another data model, the entity–relationship model, emerged in 1976 and gained popularity for database design as it emphasized a more familiar description than the earlier relational model. Later on, entity–relationship constructs were retrofitted as a data modeling construct for the relational model, and the difference between the two have become irrelevant.


1980s, on the desktop

The 1980s ushered in the age of Desktop Computer, desktop computing. The new computers empowered their users with spreadsheets like Lotus 1-2-3 and database software like dBASE. The dBASE product was lightweight and easy for any computer user to understand out of the box. C. Wayne Ratliff, the creator of dBASE, stated: "dBASE was different from programs like BASIC, C, FORTRAN, and COBOL in that a lot of the dirty work had already been done. The data manipulation is done by dBASE instead of by the user, so the user can concentrate on what he is doing, rather than having to mess with the dirty details of opening, reading, and closing files, and managing space allocation." dBASE was one of the top selling software titles in the 1980s and early 1990s.


1990s, object-oriented

The 1990s, along with a rise in object-oriented programming, saw a growth in how data in various databases were handled. Programmers and designers began to treat the data in their databases as object (computer science), objects. That is to say that if a person's data were in a database, that person's attributes, such as their address, phone number, and age, were now considered to belong to that person instead of being extraneous data. This allows for relations between data to be relations to objects and their property (programming), attributes and not to individual fields. The term "
object–relational impedance mismatch The object–relational impedance mismatch is a set of conceptual and technical difficulties that are often encountered when a relational database management system (RDBMS) is being served by an application program (or multiple application programs ...
" described the inconvenience of translating between programmed objects and database tables.
Object database An object database is a database management system In computing Computing is any goal-oriented activity requiring, benefiting from, or creating computing machinery. It includes the study and experimentation of algorithmic processes and de ...
s and
object–relational database An object–relational database (ORD), or object–relational database management system (ORDBMS), is a database management system In computing Computing is any goal-oriented activity requiring, benefiting from, or creating computing machiner ...
s attempt to solve this problem by providing an object-oriented language (sometimes as extensions to SQL) that programmers can use as alternative to purely relational SQL. On the programming side, libraries known as object–relational mappings (ORMs) attempt to solve the same problem.


2000s, NoSQL and NewSQL

XML databases are a type of structured document-oriented database that allows querying based on XML document attributes. XML databases are mostly used in applications where the data is conveniently viewed as a collection of documents, with a structure that can vary from the very flexible to the highly rigid: examples include scientific articles, patents, tax filings, and personnel records.
NoSQL A NoSQL (originally referring to "non-SQL SQL ( ''S-Q-L'', "sequel"; Structured Query Language) is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or fo ...
databases are often very fast, do not require fixed table schemas, avoid join operations by storing denormalization, denormalized data, and are designed to horizontal scaling, scale horizontally. In recent years, there has been a strong demand for massively distributed databases with high partition tolerance, but according to the CAP theorem it is impossible for a distributed computing, distributed system to simultaneously provide consistency model, consistency, availability, and partition tolerance guarantees. A distributed system can satisfy any two of these guarantees at the same time, but not all three. For that reason, many NoSQL databases are using what is called eventual consistency to provide both availability and partition tolerance guarantees with a reduced level of data consistency.
NewSQL NewSQL is a class of relational database management system In computing Computing is any goal-oriented activity requiring, benefiting from, or creating computing machinery. It includes the study and experimentation of algorithmic processes an ...
is a class of modern relational databases that aims to provide the same scalable performance of NoSQL systems for online transaction processing (read-write) workloads while still using SQL and maintaining the ACID (computer science), ACID guarantees of a traditional database system.


Use cases

Databases are used to support internal operations of organizations and to underpin online interactions with customers and suppliers (see Enterprise software). Databases are used to hold administrative information and more specialized data, such as engineering data or economic models. Examples include computerized library systems, flight reservation systems, computerized parts inventory systems, and many content management systems that store websites as collections of webpages in a database.


Classification

One way to classify databases involves the type of their contents, for example: bibliographic database, bibliographic, document-text, statistical, or multimedia objects. Another way is by their application area, for example: accounting, music compositions, movies, banking, manufacturing, or insurance. A third way is by some technical aspect, such as the database structure or interface type. This section lists a few of the adjectives used to characterize different kinds of databases. * An in-memory database is a database that primarily resides in main memory, but is typically backed-up by non-volatile computer data storage. Main memory databases are faster than disk databases, and so are often used where response time is critical, such as in telecommunications network equipment. * An active database includes an event-driven architecture which can respond to conditions both inside and outside the database. Possible uses include security monitoring, alerting, statistics gathering and authorization. Many databases provide active database features in the form of database triggers. * A cloud database relies on Cloud computing, cloud technology. Both the database and most of its DBMS reside remotely, "in the cloud", while its applications are both developed by programmers and later maintained and used by end-users through a web browser and Open APIs. * Data warehouses archive data from operational databases and often from external sources such as market research firms. The warehouse becomes the central source of data for use by managers and other end-users who may not have access to operational data. For example, sales data might be aggregated to weekly totals and converted from internal product codes to use Universal Product Code, UPCs so that they can be compared with ACNielsen data. Some basic and essential components of data warehousing include extracting, analyzing, and Data mining, mining data, transforming, loading, and managing data so as to make them available for further use. * A deductive database combines logic programming with a relational database. * A distributed database is one in which both the data and the DBMS span multiple computers. * A
document-oriented database A document-oriented database, or document store, is a computer program In imperative programming, a computer program is a sequence of instructions in a programming language that a computer can execute or interpret. In declarative programming, ...
is designed for storing, retrieving, and managing document-oriented, or semi structured, information. Document-oriented databases are one of the main categories of NoSQL databases. * An embedded database system is a DBMS which is tightly integrated with an application software that requires access to stored data in such a way that the DBMS is hidden from the application's end-users and requires little or no ongoing maintenance. *End-user databases consist of data developed by individual end-users. Examples of these are collections of documents, spreadsheets, presentations, multimedia, and other files. Several products exist to support such databases. Some of them are much simpler than full-fledged DBMSs, with more elementary DBMS functionality. * A federated database system comprises several distinct databases, each with its own DBMS. It is handled as a single database by a federated database management system (FDBMS), which transparently integrates multiple autonomous DBMSs, possibly of different types (in which case it would also be a heterogeneous database system), and provides them with an integrated conceptual view. * Sometimes the term ''multi-database'' is used as a synonym to federated database, though it may refer to a less integrated (e.g., without an FDBMS and a managed integrated schema) group of databases that cooperate in a single application. In this case, typically Middleware (distributed applications), middleware is used for distribution, which typically includes an atomic commit protocol (ACP), e.g., the two-phase commit protocol, to allow Distributed transaction, distributed (global) transactions across the participating databases. * A graph database is a kind of NoSQL database that uses Graph (data structure), graph structures with nodes, edges, and properties to represent and store information. General graph databases that can store any graph are distinct from specialized graph databases such as triplestores and network database model, network databases. * An array DBMS is a kind of NoSQL DBMS that allows modeling, storage, and retrieval of (usually large) multi-dimensional Array data structure, arrays such as satellite images and climate simulation output. * In a hypertext or hypermedia database, any word or a piece of text representing an object, e.g., another piece of text, an article, a picture, or a film, can be hyperlinked to that object. Hypertext databases are particularly useful for organizing large amounts of disparate information. For example, they are useful for organizing online encyclopedias, where users can conveniently jump around the text. The World Wide Web is thus a large distributed hypertext database. * A knowledge base (abbreviated KB, kb or Δ) is a special kind of database for knowledge management, providing the means for the computerized collection, organization, and Information retrieval, retrieval of knowledge. Also a collection of data representing problems with their solutions and related experiences. * A mobile database can be carried on or synchronized from a mobile computing device. * Operational databases store detailed data about the operations of an organization. They typically process relatively high volumes of updates using transaction (database), transactions. Examples include Customer relationship management, customer databases that record contact, credit, and demographic information about a business's customers, personnel databases that hold information such as salary, benefits, skills data about employees, enterprise resource planning systems that record details about product components, parts inventory, and financial databases that keep track of the organization's money, accounting and financial dealings. * A parallel database seeks to improve performance through Parallel computing, parallelization for tasks such as loading data, building indexes and evaluating queries. ::The major parallel DBMS architectures which are induced by the underlying Computer hardware, hardware architecture are: ::* Shared memory architecture, where multiple processors share the main memory space, as well as other data storage. ::* Shared disk architecture, where each processing unit (typically consisting of multiple processors) has its own main memory, but all units share the other storage. ::* Shared-nothing architecture, where each processing unit has its own main memory and other storage. * Probabilistic databases employ fuzzy logic to draw inferences from imprecise data. * Real-time databases process transactions fast enough for the result to come back and be acted on right away. * A spatial database can store the data with multidimensional features. The queries on such data include location-based queries, like "Where is the closest hotel in my area?". * A temporal database has built-in time aspects, for example a temporal data model and a temporal version of
SQL SQL ( ''S-Q-L'', "sequel"; Structured Query Language) is a domain-specific languageA domain-specific language (DSL) is a computer languageA computer language is a method of communication with a computer A computer is a machine that can b ...

SQL
. More specifically the temporal aspects usually include valid-time and transaction-time. * A terminology-oriented database builds upon an object-oriented database, often customized for a specific field. * An unstructured data database is intended to store in a manageable and protected way diverse objects that do not fit naturally and conveniently in common databases. It may include email messages, documents, journals, multimedia objects, etc. The name may be misleading since some objects can be highly structured. However, the entire possible object collection does not fit into a predefined structured framework. Most established DBMSs now support unstructured data in various ways, and new dedicated DBMSs are emerging.


Database management system

Connolly and Begg define database management system (DBMS) as a "software system that enables users to define, create, maintain and control access to the database". Examples of DBMS's include
MySQL MySQL () is an open-source Open source is source code that is made freely available for possible modification and redistribution. Products include permission to use the source code, design documents, or content of the product. The open-source m ...
, PostgreSQL,
Microsoft SQL Server Microsoft SQL Server is a relational database management system A relational database is a digital database based on the relational model of data, as proposed by E. F. Codd in 1970. A system used to maintain relational databases is a relational ...
, Oracle Database, and Microsoft Access. The DBMS acronym is sometimes extended to indicate the underlying
database model A database model is a type of data model A data model (or datamodel) is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities. For instance, a data model may ...
, with RDBMS for the Relational model, relational, OODBMS for the Object model, object (oriented) and ORDBMS for the object–relational_database, object–relational model. Other extensions can indicate some other characteristic, such as DDBMS for a distributed database management systems. The functionality provided by a DBMS can vary enormously. The core functionality is the storage, retrieval and update of data. Edgar F. Codd, Codd proposed the following functions and services a fully-fledged general purpose DBMS should provide: * Data storage, retrieval and update * User accessible catalog or data dictionary describing the metadata * Support for transactions and concurrency * Facilities for recovering the database should it become damaged * Support for authorization of access and update of data * Access support from remote locations * Enforcing constraints to ensure data in the database abides by certain rules It is also generally to be expected the DBMS will provide a set of utilities for such purposes as may be necessary to administer the database effectively, including import, export, monitoring, defragmentation and analysis utilities. The core part of the DBMS interacting between the database and the application interface sometimes referred to as the database engine. Often DBMSs will have configuration parameters that can be statically and dynamically tuned, for example the maximum amount of main memory on a server the database can use. The trend is to minimize the amount of manual configuration, and for cases such as embedded databases the need to target zero-administration is paramount. The large major enterprise DBMSs have tended to increase in size and functionality and can have involved thousands of human years of development effort through their lifetime. Early multi-user DBMS typically only allowed for the application to reside on the same computer with access via Computer terminal, terminals or terminal emulation software. The client–server architecture was a development where the application resided on a client desktop and the database on a server allowing the processing to be distributed. This evolved into a multitier architecture incorporating application servers and web servers with the end user interface via a web browser with the database only directly connected to the adjacent tier. A general-purpose DBMS will provide public application programming interfaces (API) and optionally a processor for database languages such as
SQL SQL ( ''S-Q-L'', "sequel"; Structured Query Language) is a domain-specific languageA domain-specific language (DSL) is a computer languageA computer language is a method of communication with a computer A computer is a machine that can b ...

SQL
to allow applications to be written to interact with the database. A special purpose DBMS may use a private API and be specifically customized and linked to a single application. For example, an email system performing many of the functions of a general-purpose DBMS such as message insertion, message deletion, attachment handling, blocklist lookup, associating messages an email address and so forth however these functions are limited to what is required to handle email.


Application

External interaction with the database will be via an application program that interfaces with the DBMS. This can range from a Comparison of database tools, database tool that allows users to execute SQL queries textually or graphically, to a web site that happens to use a database to store and search information.


Application program interface

A programmer will Computer programming, code interactions to the database (sometimes referred to as a datasource) via an application program interface (API) or via a #database language, database language. The particular API or language chosen will need to be supported by DBMS, possible indirectly via a preprocessor or a bridging API. Some API's aim to be database independent, ODBC being a commonly known example. Other common API's include JDBC and ADO.NET.


Database languages

Database languages are special-purpose languages, which allow one or more of the following tasks, sometimes distinguished as sublanguages: * Data control language (DCL) – controls access to data; * Data definition language (DDL) – defines data types such as creating, altering, or dropping tables and the relationships among them; * Data manipulation language (DML) – performs tasks such as inserting, updating, or deleting data occurrences; * Data query language (DQL) – allows searching for information and computing derived information. Database languages are specific to a particular data model. Notable examples include: * SQL combines the roles of data definition, data manipulation, and query in a single language. It was one of the first commercial languages for the relational model, although it departs in some respects from Codd's 12 rules, the relational model as described by Codd (for example, the rows and columns of a table can be ordered). SQL became a standard of the American National Standards Institute (ANSI) in 1986, and of the International Organization for Standardization (ISO) in 1987. The standards have been regularly enhanced since and is supported (with varying degrees of conformance) by all mainstream commercial relational DBMSs. * Object Query Language, OQL is an object model language standard (from the Object Data Management Group). It has influenced the design of some of the newer query languages like JDOQL and EJB QL. *
XQuery XQuery (XML Query) is a query and functional programming In computer science Computer science deals with the theoretical foundations of information, algorithms and the architectures of its computation as well as practical techniques ...
is a standard XML query language implemented by XML database systems such as MarkLogic and eXist, by relational databases with XML capability such as Oracle and DB2, and also by in-memory XML processors such as Saxon XSLT, Saxon. * SQL/XML combines
XQuery XQuery (XML Query) is a query and functional programming In computer science Computer science deals with the theoretical foundations of information, algorithms and the architectures of its computation as well as practical techniques ...
with SQL. A database language may also incorporate features like: * DBMS-specific configuration and storage engine management * Computations to modify query results, like counting, summing, averaging, sorting, grouping, and cross-referencing * Constraint enforcement (e.g. in an automotive database, only allowing one engine type per car) * Application programming interface version of the query language, for programmer convenience


Storage

Database storage is the container of the physical materialization of a database. It comprises the ''internal'' (physical) ''level'' in the database architecture. It also contains all the information needed (e.g., metadata, "data about the data", and internal data structures) to reconstruct the ''conceptual level'' and ''external level'' from the internal level when needed. Databases as digital objects contain three layers of information which must be stored: the data, the structure, and the semantics. Proper storage of all three layers is needed for future Database preservation, preservation and longevity of the database. Putting data into permanent storage is generally the responsibility of the database engine a.k.a. "storage engine". Though typically accessed by a DBMS through the underlying operating system (and often using the operating systems' file systems as intermediates for storage layout), storage properties and configuration setting are extremely important for the efficient operation of the DBMS, and thus are closely maintained by database administrators. A DBMS, while in operation, always has its database residing in several types of storage (e.g., memory and external storage). The database data and the additional needed information, possibly in very large amounts, are coded into bits. Data typically reside in the storage in structures that look completely different from the way the data look in the conceptual and external levels, but in ways that attempt to optimize (the best possible) these levels' reconstruction when needed by users and programs, as well as for computing additional types of needed information from the data (e.g., when querying the database). Some DBMSs support specifying which character encoding was used to store data, so multiple encodings can be used in the same database. Various low-level database storage structures are used by the storage engine to serialize the data model so it can be written to the medium of choice. Techniques such as indexing may be used to improve performance. Conventional storage is row-oriented, but there are also column-oriented DBMS, column-oriented and correlation databases.


Materialized views

Often storage redundancy is employed to increase performance. A common example is storing ''materialized views'', which consist of frequently needed ''external views'' or query results. Storing such views saves the expensive computing of them each time they are needed. The downsides of materialized views are the overhead incurred when updating them to keep them synchronized with their original updated database data, and the cost of storage redundancy.


Replication

Occasionally a database employs storage redundancy by database objects replication (with one or more copies) to increase data availability (both to improve performance of simultaneous multiple end-user accesses to a same database object, and to provide resiliency in a case of partial failure of a distributed database). Updates of a replicated object need to be synchronized across the object copies. In many cases, the entire database is replicated.


Security

Database security deals with all various aspects of protecting the database content, its owners, and its users. It ranges from protection from intentional unauthorized database uses to unintentional database accesses by unauthorized entities (e.g., a person or a computer program). Database access control deals with controlling who (a person or a certain computer program) is allowed to access what information in the database. The information may comprise specific database objects (e.g., record types, specific records, data structures), certain computations over certain objects (e.g., query types, or specific queries), or using specific access paths to the former (e.g., using specific indexes or other data structures to access information). Database access controls are set by special authorized (by the database owner) personnel that uses dedicated protected security DBMS interfaces. This may be managed directly on an individual basis, or by the assignment of individuals and Privilege (Computing), privileges to groups, or (in the most elaborate models) through the assignment of individuals and groups to roles which are then granted entitlements. Data security prevents unauthorized users from viewing or updating the database. Using passwords, users are allowed access to the entire database or subsets of it called "subschemas". For example, an employee database can contain all the data about an individual employee, but one group of users may be authorized to view only payroll data, while others are allowed access to only work history and medical data. If the DBMS provides a way to interactively enter and update the database, as well as interrogate it, this capability allows for managing personal databases. Data security in general deals with protecting specific chunks of data, both physically (i.e., from corruption, or destruction, or removal; e.g., see physical security), or the interpretation of them, or parts of them to meaningful information (e.g., by looking at the strings of bits that they comprise, concluding specific valid credit-card numbers; e.g., see data encryption). Change and access logging records who accessed which attributes, what was changed, and when it was changed. Logging services allow for a forensic database audit later by keeping a record of access occurrences and changes. Sometimes application-level code is used to record changes rather than leaving this to the database. Monitoring can be set up to attempt to detect security breaches.


Transactions and concurrency

Database transactions can be used to introduce some level of fault tolerance and data integrity after recovery from a Crash (computing), crash. A database transaction is a unit of work, typically encapsulating a number of operations over a database (e.g., reading a database object, writing, acquiring or releasing a Lock (database), lock, etc.), an abstraction supported in database and also other systems. Each transaction has well defined boundaries in terms of which program/code executions are included in that transaction (determined by the transaction's programmer via special transaction commands). The acronym ACID describes some ideal properties of a database transaction: Atomicity (database systems), atomicity, Consistency (database systems), consistency, Isolation (database systems), isolation, and Durability (database systems), durability.


Migration

A database built with one DBMS is not portable to another DBMS (i.e., the other DBMS cannot run it). However, in some situations, it is desirable to migrate a database from one DBMS to another. The reasons are primarily economical (different DBMSs may have different Total cost of ownership, total costs of ownership or TCOs), functional, and operational (different DBMSs may have different capabilities). The migration involves the database's transformation from one DBMS type to another. The transformation should maintain (if possible) the database related application (i.e., all related application programs) intact. Thus, the database's conceptual and external architectural levels should be maintained in the transformation. It may be desired that also some aspects of the architecture internal level are maintained. A complex or large database migration may be a complicated and costly (one-time) project by itself, which should be factored into the decision to migrate. This in spite of the fact that tools may exist to help migration between specific DBMSs. Typically, a DBMS vendor provides tools to help importing databases from other popular DBMSs.


Building, maintaining, and tuning

After designing a database for an application, the next stage is building the database. Typically, an appropriate general-purpose DBMS can be selected to be used for this purpose. A DBMS provides the needed user interfaces to be used by database administrators to define the needed application's data structures within the DBMS's respective data model. Other user interfaces are used to select needed DBMS parameters (like security related, storage allocation parameters, etc.). When the database is ready (all its data structures and other needed components are defined), it is typically populated with initial application's data (database initialization, which is typically a distinct project; in many cases using specialized DBMS interfaces that support bulk insertion) before making it operational. In some cases, the database becomes operational while empty of application data, and data are accumulated during its operation. After the database is created, initialized and populated it needs to be maintained. Various database parameters may need changing and the database may need to be tuned (Database tuning, tuning) for better performance; application's data structures may be changed or added, new related application programs may be written to add to the application's functionality, etc.


Backup and restore

Sometimes it is desired to bring a database back to a previous state (for many reasons, e.g., cases when the database is found corrupted due to a software error, or if it has been updated with erroneous data). To achieve this, a backup operation is done occasionally or continuously, where each desired database state (i.e., the values of its data and their embedding in database's data structures) is kept within dedicated backup files (many techniques exist to do this effectively). When it is decided by a database administrator to bring the database back to this state (e.g., by specifying this state by a desired point in time when the database was in this state), these files are used to restore that state.


Static analysis

Static analysis techniques for software verification can be applied also in the scenario of query languages. In particular, the *Abstract interpretation framework has been extended to the field of query languages for relational databases as a way to support sound approximation techniques. The semantics of query languages can be tuned according to suitable abstractions of the concrete domain of data. The abstraction of relational database system has many interesting applications, in particular, for security purposes, such as fine grained access control, watermarking, etc.


Miscellaneous features

Other DBMS features might include: * Database logs – This helps in keeping a history of the executed functions. * Graphics component for producing graphs and charts, especially in a data warehouse system. * Query optimizer – Performs query optimization on every query to choose an efficient ''query plan'' (a partial order (tree) of operations) to be executed to compute the query result. May be specific to a particular storage engine. * Tools or hooks for database design, application programming, application program maintenance, database performance analysis and monitoring, database configuration monitoring, DBMS hardware configuration (a DBMS and related database may span computers, networks, and storage units) and related database mapping (especially for a distributed DBMS), storage allocation and database layout monitoring, storage migration, etc. Increasingly, there are calls for a single system that incorporates all of these core functionalities into the same build, test, and deployment framework for database management and source control. Borrowing from other developments in the software industry, some market such offerings as "DevOps for database".


Design and modeling

The first task of a database designer is to produce a conceptual data model that reflects the structure of the information to be held in the database. A common approach to this is to develop an entity–relationship model, often with the aid of drawing tools. Another popular approach is the Unified Modeling Language. A successful data model will accurately reflect the possible state of the external world being modeled: for example, if people can have more than one phone number, it will allow this information to be captured. Designing a good conceptual data model requires a good understanding of the application domain; it typically involves asking deep questions about the things of interest to an organization, like "can a customer also be a supplier?", or "if a product is sold with two different forms of packaging, are those the same product or different products?", or "if a plane flies from New York to Dubai via Frankfurt, is that one flight or two (or maybe even three)?". The answers to these questions establish definitions of the terminology used for entities (customers, products, flights, flight segments) and their relationships and attributes. Producing the conceptual data model sometimes involves input from Business process modeling, business processes, or the analysis of workflow in the organization. This can help to establish what information is needed in the database, and what can be left out. For example, it can help when deciding whether the database needs to hold historic data as well as current data. Having produced a conceptual data model that users are happy with, the next stage is to translate this into a Database schema, schema that implements the relevant data structures within the database. This process is often called logical database design, and the output is a logical data model expressed in the form of a schema. Whereas the conceptual data model is (in theory at least) independent of the choice of database technology, the logical data model will be expressed in terms of a particular database model supported by the chosen DBMS. (The terms ''data model'' and ''database model'' are often used interchangeably, but in this article we use ''data model'' for the design of a specific database, and ''database model'' for the modeling notation used to express that design). The most popular database model for general-purpose databases is the relational model, or more precisely, the relational model as represented by the SQL language. The process of creating a logical database design using this model uses a methodical approach known as Database normalization, normalization. The goal of normalization is to ensure that each elementary "fact" is only recorded in one place, so that insertions, updates, and deletions automatically maintain consistency. The final stage of database design is to make the decisions that affect performance, scalability, recovery, security, and the like, which depend on the particular DBMS. This is often called ''physical database design'', and the output is the physical data model. A key goal during this stage is data independence, meaning that the decisions made for performance optimization purposes should be invisible to end-users and applications. There are two types of data independence: Physical data independence and logical data independence. Physical design is driven mainly by performance requirements, and requires a good knowledge of the expected workload and access patterns, and a deep understanding of the features offered by the chosen DBMS. Another aspect of physical database design is security. It involves both defining access control to database objects as well as defining security levels and methods for the data itself.


Models

A database model is a type of data model that determines the logical structure of a database and fundamentally determines in which manner data can be stored, organized, and manipulated. The most popular example of a database model is the relational model (or the SQL approximation of relational), which uses a table-based format. Common logical data models for databases include: *Navigational databases **Hierarchical database model **Network model **Graph database *Relational model *Entity–relationship model **Enhanced entity–relationship model *Object database, Object model *Document-oriented database, Document model *Entity–attribute–value model *Star schema An object–relational database combines the two related structures. Physical data models include: *Inverted index *Flat file database, Flat file Other models include: *Multidimensional database, Multidimensional model *Array DBMS, Array model *Multivalue model Specialized models are optimized for particular types of data: *XML database *Semantic data model, Semantic model *Content store *Event store *Time series database, Time series model


External, conceptual, and internal views

A database management system provides three views of the database data: *The external level defines how each group of end-users sees the organization of data in the database. A single database can have any number of views at the external level. *The conceptual level unifies the various external views into a compatible global view. It provides the synthesis of all the external views. It is out of the scope of the various database end-users, and is rather of interest to database application developers and database administrators. *The internal level (or ''physical level'') is the internal organization of data inside a DBMS. It is concerned with cost, performance, scalability and other operational matters. It deals with storage layout of the data, using storage structures such as Index (database), indexes to enhance performance. Occasionally it stores data of individual views (materialized views), computed from generic data, if performance justification exists for such redundancy. It balances all the external views' performance requirements, possibly conflicting, in an attempt to optimize overall performance across all activities. While there is typically only one conceptual (or logical) and physical (or internal) view of the data, there can be any number of different external views. This allows users to see database information in a more business-related way rather than from a technical, processing viewpoint. For example, a financial department of a company needs the payment details of all employees as part of the company's expenses, but does not need details about employees that are the interest of the human resources department. Thus different departments need different ''views'' of the company's database. The three-level database architecture relates to the concept of ''data independence'' which was one of the major initial driving forces of the relational model. The idea is that changes made at a certain level do not affect the view at a higher level. For example, changes in the internal level do not affect application programs written using conceptual level interfaces, which reduces the impact of making physical changes to improve performance. The conceptual view provides a level of indirection between internal and external. On one hand it provides a common view of the database, independent of different external view structures, and on the other hand it abstracts away details of how the data are stored or managed (internal level). In principle every level, and even every external view, can be presented by a different data model. In practice usually a given DBMS uses the same data model for both the external and the conceptual levels (e.g., relational model). The internal level, which is hidden inside the DBMS and depends on its implementation, requires a different level of detail and uses its own types of data structure types. Separating the ''external'', ''conceptual'' and ''internal'' levels was a major feature of the relational database model implementations that dominate 21st century databases.


Research

Database technology has been an active research topic since the 1960s, both in academia and in the research and development groups of companies (for example IBM Research). Research activity includes Database theory, theory and development of prototypes. Notable research topics have included Data model, models, the atomic transaction concept, and related concurrency control techniques, query languages and query optimization methods, RAID, and more. The database research area has several dedicated academic journals (for example, ''ACM Transactions on Database Systems''-TODS, ''Data and Knowledge Engineering''-DKE) and annual Academic conference, conferences (e.g., Association for Computing Machinery, ACM SIGMOD, ACM Symposium on Principles of Database Systems, PODS, VLDB conference, VLDB, IEEE ICDE).


See also

* Comparison of database tools * Comparison of object database management systems * Comparison of object–relational database management systems * Comparison of relational database management systems * Data hierarchy * Data bank * Data store * Database theory * Database testing * Database-centric architecture * Flat-file database * Journal of Database Management * Question-focused dataset


Notes


References


Sources

* * * * * * * * * * * * * * * *


Further reading

* Ling Liu and Tamer M. Özsu (Eds.) (2009).
Encyclopedia of Database Systems
4100 p. 60 illus. . * Gray, J. and Reuter, A. ''Transaction Processing: Concepts and Techniques'', 1st edition, Morgan Kaufmann Publishers, 1992. * Kroenke, David M. and David J. Auer. ''Database Concepts.'' 3rd ed. New York: Prentice, 2007. * Raghu Ramakrishnan and Johannes Gehrke,
Database Management Systems
' * Abraham Silberschatz, Henry F. Korth, S. Sudarshan,
Database System Concepts
' * * Teorey, T.; Lightstone, S. and Nadeau, T. ''Database Modeling & Design: Logical Design'', 4th edition, Morgan Kaufmann Press, 2005.


External links


DB File extension
nbsp;– information about files with the DB extension {{Authority control Databases, Database management systems,