Database - Wikipedia, The Free Encyclopedia

8/9/2019 Database - Wikipedia, The Free Encyclopedia

1/23

6/15/2014 Database - Wikipedia, the free encyclopedia

http://en.wikipedia.org/wiki/Database 1

DatabaseFrom Wikipedia, the free encyclopedia

A database is an organ ized collection of data. The data are typically organized to model relevantaspects o f reality in a way that supports pr ocesses requiring this information. For example, modellingthe availa bility of rooms in hotels in a way that supports finding a hotel with vacancies.

Database ma nageme nt systems (DBMS s) are specially designed software applications thatinteract with the user, other a pplications, and the database itself to capture and analyze data. Ageneral-p urpose D BMS is a software system designed to allow the definition, creation, querying,update, a nd administration of databases. Well-known DBMSs include MySQL, MariaDB,PostgreSQL, SQLite, Microsoft SQL Ser ver, Microsoft Access, Oracle, SAP HANA, dBASE,FoxPro, IBM DB2, LibreOffice Base, FileMaker Pro and InterSystems Cach. A database is notgenerally portable across different DBMSs, but different DBMSs can interoperate by using standardssuch as SQL and ODBC or JDBC to allow a single application to work with more than one database.

Content s

1 Terminology and overview2 Applications3 General-purpose and special-purpose DBMSs4 History

4.1 1960s, navigational DBMS

4.2 1970s, relational DBMS4.3 Integrated appro ach4.4 Late 1970s, SQL DBMS4.5 1980s, on the des ktop4.6 1980s, object-oriented4.7 2000s, NoSQL and NewSQL

5 Research6 Examples

7 Design and modeling7.1 Models7.2 External, conceptual, and internal views

8 Languages9 Performance, security, and availability

9.1 Storage9.1.1 Materialized views9.1.2 Replication
http://en.wikipedia.org/wiki/SQLhttp://en.wikipedia.org/wiki/ODBChttp://en.wikipedia.org/wiki/JDBChttp://en.wikipedia.org/wiki/IBM_DB2http://en.wikipedia.org/wiki/LibreOffice_Basehttp://en.wikipedia.org/wiki/FilemakerProhttp://en.wikipedia.org/wiki/PostgreSQLhttp://en.wikipedia.org/wiki/SQLitehttp://en.wikipedia.org/wiki/Microsoft_SQL_Serverhttp://en.wikipedia.org/wiki/Computer_softwarehttp://en.wikipedia.org/wiki/JDBChttp://en.wikipedia.org/wiki/ODBChttp://en.wikipedia.org/wiki/SQLhttp://en.wikipedia.org/wiki/Technical_standardhttp://en.wikipedia.org/wiki/Software_portabilityhttp://en.wikipedia.org/wiki/InterSystems_Cachehttp://en.wikipedia.org/wiki/FilemakerProhttp://en.wikipedia.org/wiki/LibreOffice_Basehttp://en.wikipedia.org/wiki/IBM_DB2http://en.wikipedia.org/wiki/FoxProhttp://en.wikipedia.org/wiki/DBASEhttp://en.wikipedia.org/wiki/SAP_HANAhttp://en.wikipedia.org/wiki/Oracle_Databasehttp://en.wikipedia.org/wiki/Microsoft_Accesshttp://en.wikipedia.org/wiki/Microsoft_SQL_Serverhttp://en.wikipedia.org/wiki/SQLitehttp://en.wikipedia.org/wiki/PostgreSQLhttp://en.wikipedia.org/wiki/MariaDBhttp://en.wikipedia.org/wiki/MySQLhttp://en.wikipedia.org/wiki/Computer_softwarehttp://en.wikipedia.org/wiki/Data_(computing)


2/23



9.2 Security9.3 Transactions and concurrency9.4 Migration9.5 Building, maintaining, and tuning9.6 Backup and restore9.7 Other

10 See also11 References12 Further reading13 External links

Terminology and overview

Formally, "database" refers to the data themselves and supporting data structures. Databases arecreated to operate large quantities of information by inputting, storing, retrieving and managing thatinformation. Databases are set up so that one set of software programs provides all users withaccess to all the data.

A "database management system" (DBMS) is a suite of computer software providing the interfacebetween users and a database or databases. Because they are so closely related, the term"database" when used casually often refers to both a DBMS and the data it manipulates.

Outside the world of professional information technology, the term database is sometimes used

casually to refer to any collection of data (perhaps a spreadsheet, maybe even a card index). Thisarticle is concerned only with databases where the size and usage requirements necessitate use of adatabase management system. [1]

The interactions catered for by most existing DBMSs fall into four main groups:

Data definition Defining new data structures for a database, removing data structures fromthe database, modifying the structure of existing data.Update Inserting, modifying, and deleting data.

Retrieval Obtaining information either for end-user queries and reports or for processing byapplications.Administration Registering and monitoring users, enforcing data security, monitoringperformance, maintaining data integrity, dealing with concurrency control, and recoveringinformation if the system fails.

A DBMS is responsible for maintaining the integrity and security of stored data, and for recoveringinformation if the system fails.
http://en.wikipedia.org/wiki/Spreadsheethttp://en.wikipedia.org/wiki/Information_technology


3/23



Both a database and its DBMS conform to the principles of a particular database model. [2]"Database system" refers collectively to the database model, database management system, anddatabase. [3]

Physically, database servers are dedicated computers that hold the actual databases and run onlythe DBMS and related software. Database servers are usually multiprocessor computers, withgenerous memory and RAID disk arrays used for stable storage. RAID is used for recovery of data if

any of the disks fail. Hardware database accelerators, connected to one or more servers via a high-speed channel, are also used in large volume transaction processing environments. DBMSs arefound at the heart of most database applications. DBMSs may be built around a custom multitaskingkernel with built-in networking support, but modern DBMSs typically rely on a standard operatingsystem to provide these functions. Since DBMSs comprise a significant economical market,computer and storage vendors often take into account DBMS requirements in their own developmentplans.

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(s) used to access the database (such as SQL or XQuery), and their internal engineering, which affects performance, scalability, resilience, and security.

Applications

Databases are used to support internal operations of organizations and to underpin onlineinteractions with customers and suppliers (see Enterprise software).

Databases are used to hold administrative information and more specialized data, such asengineering data or economic models. Examples of database applications include computerizedlibrary systems, flight reservation systems and computerized parts inventory systems.

General-purpose and special-purpose DBMSs

A DBMS has evolved into a complex software system and its development typically requiresthousands of person-years of development effort. [4] Some general-purpose DBMSs such as

Adabas, Oracle and DB2 have been undergoing upgrades since the 1970s. General-purposeDBMSs aim to meet the needs of as many applications as possible, which adds to the complexity.However, the fact that their development cost can be spread over a large number of users means that

they are often the most cost-effective approach. However, a general-purpose DBMS is not alwaysthe optimal solution: in some cases a general-purpose DBMS may introduce unnecessary overhead.Therefore, there are many examples of systems that use special-purpose databases. A commonexample is an email system: email systems are designed to optimize the handling of emailmessages, and do not need significant portions of a general-purpose DBMS functionality.

Many databases have application software that accesses the database on behalf of end-users,without exposing the DBMS interface directly. Application programmers may use a wire protocoldirectly, or more likely through an application programming interface. Database designers and
http://en.wikipedia.org/wiki/Application_programming_interfacehttp://en.wikipedia.org/wiki/Wire_protocolhttp://en.wikipedia.org/wiki/Application_softwarehttp://en.wikipedia.org/wiki/Emailhttp://en.wikipedia.org/wiki/Oracle_Corporationhttp://en.wikipedia.org/wiki/Adabashttp://en.wikipedia.org/wiki/Parts_inventory_systemhttp://en.wikipedia.org/wiki/Flight_reservation_systemhttp://en.wikipedia.org/wiki/Libraryhttp://en.wikipedia.org/wiki/Enterprise_softwarehttp://en.wikipedia.org/wiki/Scalabilityhttp://en.wikipedia.org/wiki/XQueryhttp://en.wikipedia.org/wiki/Query_languagehttp://en.wikipedia.org/wiki/Market_(economics)http://en.wikipedia.org/wiki/Economyhttp://en.wikipedia.org/wiki/Operating_systemhttp://en.wikipedia.org/wiki/Computer_networkhttp://en.wikipedia.org/wiki/Kernel_(computing)http://en.wikipedia.org/wiki/Computer_multitaskinghttp://en.wikipedia.org/wiki/Database_applicationhttp://en.wikipedia.org/wiki/Redundant_array_of_independent_diskshttp://en.wikipedia.org/wiki/Multiprocessorhttp://en.wikipedia.org/wiki/Server_(computing)http://en.wikipedia.org/wiki/Database_model


4/23



database administrators interact with the DBMS through dedicated interfaces to build and maintainthe applications' databases, and thus need some more knowledge and understanding about howDBMSs operate and the DBMSs' external interfaces and tuning parameters.

History

Following the technology progress in the areas of processors, computer memory, computer storageand computer networks, the sizes, capabilities, and performance of databases and their respectiveDBMSs have grown in orders of magnitude. The development of database technology can bedivided into three eras based on data model or structure: navigational, [5] SQL/relational, and post-relational.

The two main early navigational data models were the hierarchical model, epitomized by IBM's IMSsystem, and the CODASYL model (network model), implemented in a number of products such asIDMS.

The relational model, first proposed in 1970 by Edgar F. Codd, departed from this tradition by

insisting that applications should search for data by content, rather than by following links. Therelational model employs sets of ledger-style tables, each used for a different type of entity. Only inthe mid-1980s did computing hardware became powerful enough to allow the wide deployment of relational systems (DBMSs plus applications). By the early 1990s, however, relational systemsdominated in all large-scale data processing applications, and as of 2014 they remain dominantexcept in niche areas. The dominant database language, standardised SQL for the relational model,has influenced database languages for other data models.

Object databases developed in the 1980s to overcome the inconvenience of object-relationalimpedance mismatch, which led to the coining of the term "post-relational" and also the development

of hybrid object-relational databases.The next generation of post-relational databases in the late 2000s became known as NoSQLdatabases, introducing fast key-value stores and document-oriented databases. A competing "nextgeneration" known as NewSQL databases attempted new implementations that retained therelational/SQL model while aiming to match the high performance of NoSQL compared tocommercially available relational DBMSs.

1960s, navigational DBMS

The introduction of the term database coincided with the availability of direct-access storage (disksand drums) from the mid-1960s onwards. The term represented a contrast with the tape-basedsystems of the past, allowing shared interactive use rather than daily batch processing. The OxfordEnglish dictionary cites [6] a 1962 report by the System Development Corporation of California as thefirst to use the term "data-base" in a specific technical sense.

As computers grew in speed and capability, a number of general-purpose database systemsemerged; by the mid-1960s a number of such systems had come into commercial use. Interest in astandard began to grow, and Charles Bachman, author of one such product, the Integrated DataStore (IDS), founded the "Database Task Group" within CODASYL, the group responsible for the
http://en.wikipedia.org/wiki/CODASYLhttp://en.wikipedia.org/wiki/Integrated_Data_Storehttp://en.wikipedia.org/wiki/Charles_Bachmanhttp://en.wikipedia.org/wiki/Oxford_English_dictionaryhttp://en.wikipedia.org/wiki/Batch_processinghttp://en.wikipedia.org/wiki/NewSQLhttp://en.wikipedia.org/wiki/Document-oriented_databasehttp://en.wikipedia.org/wiki/Key-value_storehttp://en.wikipedia.org/wiki/NoSQLhttp://en.wikipedia.org/wiki/Object-relational_databasehttp://en.wikipedia.org/wiki/Object-relational_impedance_mismatchhttp://en.wikipedia.org/wiki/Object_databasehttp://en.wikipedia.org/wiki/Edgar_F._Coddhttp://en.wikipedia.org/wiki/Relational_modelhttp://en.wikipedia.org/wiki/IDMShttp://en.wikipedia.org/wiki/Network_modelhttp://en.wikipedia.org/wiki/CODASYLhttp://en.wikipedia.org/wiki/Hierarchical_database_modelhttp://en.wikipedia.org/wiki/Relational_databasehttp://en.wikipedia.org/wiki/Navigational_databasehttp://en.wikipedia.org/wiki/Computer_networkshttp://en.wikipedia.org/wiki/Computer_storagehttp://en.wikipedia.org/wiki/Computer_memoryhttp://en.wikipedia.org/wiki/Processors


5/23



Basic structure of navigational CODASYLdatabase model.

creation and standardization of COBOL. In 1971 the Database Task Group delivered their standard,which generally became known as the "CODASYL approach", and soon a number of commercialproducts based on this approach entered the market.

The CODASYL approach relied on the "manual" navigation of a linked data set which was formedinto 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)navigating relationships (called sets) from one record to another scanning all the records in a sequential order.

Later systems added B-Trees to provide alternateaccess paths. Many CODASYL databases also addeda very straightforward query language. However, in thefinal tally, CODASYL was very complex and requiredsignificant training and effort to produce usefulapplications.

IBM also had their own DBMS in 1968, known as IMS .IMS was a development of software written for the

Apollo program on the System/360. IMS was generallysimilar in concept to CODASYL, but used a stricthierarchy for its model of data navigation instead of CODASYL's network model. Both concepts later became known as navigational databases due to theway data was accessed, and Bachman's 1973 Turing

Award presentation was The Programmer as

Navigator . IMS is classified as a hierarchicaldatabase. IDMS and Cincom Systems' TOTALdatabase are classified as network databases. IMSremains in use as of 2014. [7]

1970s, relational DBMS

Edgar Codd worked at IBM in San Jose, California, inone of their offshoot offices that was primarily involvedin the development of hard disk systems. He wasunhappy with the navigational model of the CODASYLapproach, notably the lack of a "search" facility. In 1970, he wrote a number of papers that outlined anew approach to database construction that eventually culminated in the groundbreaking ARelational Model of Data for Large Shared Data Banks .[8]

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 ideawas to use a "table" of fixed-length records, with each table used for a different type of entity. Alinked-list system would be very inefficient when storing "sparse" databases where some of the datafor any one record could be left empty. The relational model solved this by splitting the data into a
http://en.wikipedia.org/wiki/Table_(database)http://en.wikipedia.org/wiki/Linked_listhttp://en.wikipedia.org/wiki/Hard_diskhttp://en.wikipedia.org/wiki/San_Jose,_Californiahttp://en.wikipedia.org/wiki/Edgar_Coddhttp://en.wikipedia.org/wiki/Cincom_Systems#1970shttp://en.wikipedia.org/wiki/Cincom_Systemshttp://en.wikipedia.org/wiki/Hierarchical_databasehttp://en.wikipedia.org/wiki/Turing_Awardhttp://en.wikipedia.org/wiki/System/360http://en.wikipedia.org/wiki/Apollo_programhttp://en.wikipedia.org/wiki/Information_Management_Systemhttp://en.wikipedia.org/wiki/International_Business_Machineshttp://en.wikipedia.org/wiki/COBOLhttp://en.wikipedia.org/wiki/CODASYLhttp://en.wikipedia.org/wiki/File:CodasylB.png


6/23



In the relational model, related records arelinked together with a "key"

series of normalized tables (or relations ), with optional elements being moved out of the main tableto where they would take up room only if needed. Data may be freely inserted, deleted and edited inthese tables, with the DBMS doing whatever maintenance needed to present a table view to theapplication/user.

The relational model also allowed the content of thedatabase to evolve without constant rewriting of linksand pointers. The relational part comes from entitiesreferencing other entities in what is known as one-to-many relationship, like a traditional hierarchicalmodel, and many-to-many relationship, like anavigational (network) model. Thus, a relationalmodel can express both hierarchical andnavigational models, as well as its native tabular model, allowing for pure or combined modeling interms of these three models, as the applicationrequires.

For instance, a common use of a database systemis to track information about users, their name, logininformation, various addresses and phone numbers.In the navigational approach all of these data wouldbe placed in a single record, and unused itemswould simply not be placed in the database. In the relational approach, the data would be normalizedinto a user table, an address table and a phone number table (for instance). Records would becreated in these optional tables only if the address or phone numbers were actually provided.

Linking the information back together is the key to this system. In the relational model, some bit of

information was used as a "key", uniquely defining a particular record. When information was beingcollected about a user, information stored in the optional tables would be found by searching for thiskey. For instance, if the login name of a user is unique, addresses and phone numbers for that user would be recorded with the login name as its key. This simple "re-linking" of related data back into asingle collection is something that traditional computer languages are not designed for.

Just as the navigational approach would require programs to loop in order to collect records, therelational approach would require loops to collect information about any one record. Codd's solutionto the necessary looping was a set-oriented language, a suggestion that would later spawn theubiquitous SQL. Using a branch of mathematics known as tuple calculus, he demonstrated that such

a system could support all the operations of normal databases (inserting, updating etc.) as well asproviding a simple system for finding and returning sets of data in a single operation.

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 ageographical 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 System R in a number of ways, including the use of a "language" for dataaccess, known as 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, Business
http://en.wikipedia.org/wiki/Business_System_12http://en.wikipedia.org/wiki/Business_System_12http://en.wikipedia.org/wiki/PRTVhttp://en.wikipedia.org/wiki/QUEL_query_languageshttp://en.wikipedia.org/wiki/IBM_System_Rhttp://en.wikipedia.org/wiki/INGREShttp://en.wikipedia.org/wiki/Michael_Stonebrakerhttp://en.wikipedia.org/w/index.php?title=Eugene_Wong&action=edit&redlink=1http://en.wikipedia.org/wiki/Tuple_calculushttp://en.wikipedia.org/wiki/Primary_keyhttp://en.wikipedia.org/wiki/Relational_modelhttp://en.wikipedia.org/wiki/File:Relational_key_SVG.svg


7/23



System 12, both now discontinued. Honeywell wrote MRDS for Multics, and now there are two newimplementations: Alphora Dataphor and Rel. Most other DBMS implementations usually calledrelational are actually SQL DBMSs.

In 1970, the University of Michigan began development of the MICRO Information ManagementSystem [9] based on D.L. Childs' Set-Theoretic Data model. [10][11][12] Micro was used to managevery large data sets by the US Department of Labor, the U.S. Environmental Protection Agency, andresearchers from the University of Alberta, the University of Michigan, and Wayne State University. Itran on IBM mainframe computers using the Michigan Terminal System. [13] The system remained inproduction until 1998.

Integrated approach

In the 1970s and 1980s attempts were made to build database systems with integrated hardwareand software. The underlying philosophy was that such integration would provide higher performanceat 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 ICL's CAFS accelerator, ahardware disk controller with programmable search capabilities. In the long term, these efforts weregenerally unsuccessful because specialized database machines could not keep pace with the rapiddevelopment and progress of general-purpose computers. Thus most database systems nowadaysare software systems running on general-purpose hardware, using general-purpose computer datastorage. However this idea is still pursued for certain applications by some companies like Netezzaand Oracle (Exadata).

Late 1970s, SQL DBMS

IBM started working on a prototype system loosely based on Codd's concepts as System R in theearly 1970s. The first version was ready in 1974/5, and work then started on multi-table systems inwhich the data could be split so that all of the data for a record (some of which is optional) did nothave to be stored in a single large "chunk". Subsequent multi-user versions were tested bycustomers in 1978 and 1979, by which time a standardized query language SQL had beenadded. 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 (DB2).

Larry Ellison's Oracle started from a different chain, based on IBM's papers on System R, and beatIBM to market when the first version was released in 1978.

Stonebraker went on to apply the lessons from INGRES to develop a new database, Postgres, whichis 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 companiesand financial institutions).
http://en.wikipedia.org/wiki/Business_System_12http://en.wikipedia.org/wiki/Larry_Ellisonhttp://en.wikipedia.org/wiki/Query_languagehttp://en.wikipedia.org/wiki/Exadatahttp://en.wikipedia.org/wiki/Netezzahttp://en.wikipedia.org/wiki/Content_Addressable_File_Storehttp://en.wikipedia.org/wiki/International_Computers_Limitedhttp://en.wikipedia.org/wiki/Britton_Lee,_Inc.http://en.wikipedia.org/wiki/Teradatahttp://en.wikipedia.org/wiki/System/38http://en.wikipedia.org/wiki/Michigan_Terminal_Systemhttp://en.wikipedia.org/wiki/Wayne_State_Universityhttp://en.wikipedia.org/wiki/University_of_Michiganhttp://en.wikipedia.org/wiki/University_of_Albertahttp://en.wikipedia.org/wiki/U.S._Environmental_Protection_Agencyhttp://en.wikipedia.org/wiki/US_Department_of_Laborhttp://en.wikipedia.org/wiki/MICRO_Information_Management_Systemhttp://en.wikipedia.org/wiki/Rel_(DBMS)http://en.wikipedia.org/wiki/Dataphorhttp://en.wikipedia.org/wiki/Multicshttp://en.wikipedia.org/wiki/Multics_Relational_Data_Storehttp://en.wikipedia.org/wiki/Honeywellhttp://en.wikipedia.org/wiki/Business_System_12


8/23



In Sweden, Codd's paper was also read and Mimer SQL was developed from the mid-1970s atUppsala University. In 1984, this project was consolidated into an independent enterprise. In the early1980s, Mimer introduced transaction handling for high robustness in applications, an idea that wassubsequently implemented on most other DBMSs.

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 relationalmodel, and the difference between the two have become irrelevant.

1980s, on the desktop

The 1980s ushered in the age of desktop computing. The new computers empowered their userswith spreadsheets like Lotus 1,2,3 and database software like dBASE. The dBASE product waslightweight 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 inthat a lot of the dirty work had already been done. The data manipulation is done by dBASE insteadof by the user, so the user can concentrate on what he is doing, rather than having to mess with thedirty details of opening, reading, and closing files, and managing space allocation. [14] dBASE wasone of the top selling software titles in the 1980s and early 1990s.

1980s, object-oriented

The 1980s, along with a rise in object-oriented programming, saw a growth in how data in variousdatabases were handled. Programmers and designers began to treat the data in their databases asobjects. That is to say that if a person's data were in a database, that person's attributes, such astheir 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 attributes and not to individual fields.[15] The term "object-relational impedance mismatch" describedthe inconvenience of translating between programmed objects and database tables. Objectdatabases and object-relational databases attempt to solve this problem by providing an object-oriented language (sometimes as extensions to SQL) that programmers can use as alternative topurely relational SQL. On the programming side, libraries known as object-relational mappings(ORMs) attempt to solve the same problem.

2000s, NoSQL and NewSQL

The next generation of post-relational databases in the 2000s became known as NoSQL databases,including fast key-value stores and document-oriented databases. XML databases are a type of structured document-oriented database that allows querying based on XML document attributes.XML databases are mostly used in enterprise database management, where XML is being used asthe machine-to-machine data interoperability standard. XML databases are mostly commercialsoftware systems, that include Clusterpoint, [16] MarkLogic[17] and Oracle XML DB.[18]

NoSQL databases are often very fast, do not require fixed table schemas, avoid join operations bystoring denormalized data, and are designed to scale horizontally. The most popular NoSQL systemsinclude MongoDB, Couchbase, Riak, memcached, Redis, CouchDB, Hazelcast, Apache Cassandra
http://en.wikipedia.org/wiki/Apache_Cassandrahttp://en.wikipedia.org/wiki/Hazelcasthttp://en.wikipedia.org/wiki/CouchDBhttp://en.wikipedia.org/wiki/Redishttp://en.wikipedia.org/wiki/Memcachedhttp://en.wikipedia.org/wiki/Riakhttp://en.wikipedia.org/wiki/Couchbasehttp://en.wikipedia.org/wiki/MongoDBhttp://en.wikipedia.org/wiki/Horizontal_scalinghttp://en.wikipedia.org/wiki/Denormalizationhttp://en.wikipedia.org/wiki/Oracle_Databasehttp://en.wikipedia.org/wiki/MarkLogichttp://en.wikipedia.org/wiki/Clusterpointhttp://en.wikipedia.org/wiki/Enterprise_database_managementhttp://en.wikipedia.org/wiki/XMLhttp://en.wikipedia.org/wiki/XML_databaseshttp://en.wikipedia.org/wiki/Object-relational_mappinghttp://en.wikipedia.org/wiki/Object-oriented_programminghttp://en.wikipedia.org/wiki/C._Wayne_Ratliffhttp://en.wikipedia.org/wiki/Desktop_Computerhttp://en.wikipedia.org/wiki/Database_designhttp://en.wikipedia.org/wiki/Entity-relationship_modelhttp://en.wikipedia.org/wiki/Uppsala_Universityhttp://en.wikipedia.org/wiki/Mimer_SQL


9/23



and HBase, [19] which are all open-source software products.

In recent years there was a high demand for massively distributed databases with high partitiontolerance but according to the CAP theorem it is impossible for a distributed system tosimultaneously provide consistency, availability and partition tolerance guarantees. A distributedsystem can satisfy any two of these guarantees at the same time, but not all three. For that reasonmany NoSQL databases are using what is called eventual consistency to provide both availabilityand partition tolerance guarantees with a maximum level of data consistency.

NewSQL is a class of modern relational databases that aims to provide the same scalableperformance of NoSQL systems for online transaction processing (read-write) workloads while stillusing SQL and maintaining the ACID guarantees of a traditional database system. Such databasesinclude Clustrix, EnterpriseDB, NuoDB[20] and VoltDB.

Research

Database technology has been an active research topic since the 1960s, both in academia and inthe research and development groups of companies (for example IBM Research). Research activityincludes theory and development of prototypes. Notable research topics have included models, theatomic transaction concept and related concurrency control techniques, query languages and queryoptimization 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 annualconferences (e.g., ACM SIGMOD, ACM PODS, VLDB, IEEE ICDE).

ExamplesOne way to classify databases involves the type of their contents, for example: 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 wayis by some technical aspect, such as the database structure or interface type. This section lists a fewof the adjectives used to characterize different kinds of databases.

An in-memory database is a database that primarily resides in main memory, but is typicallybacked-up by non-volatile computer data storage. Main memory databases are faster than diskdatabases, and so are often used where response time is critical, such as intelecommunications network equipment. [21]SAP HANA platform is a very hot topic for in-memory database. By May 2012, HANA was able to run on servers with 100TB main memorypowered by IBM. The co founder of the company claimed that the system was big enough to runthe 8 largest SAP customers.

An active database includes an event-driven architecture which can respond to conditions bothinside and outside the database. Possible uses include security monitoring, alerting, statistics
http://en.wikipedia.org/wiki/Active_databasehttp://en.wikipedia.org/wiki/SAP_HANAhttp://en.wikipedia.org/wiki/Main_memoryhttp://en.wikipedia.org/wiki/In-memory_databasehttp://en.wikipedia.org/wiki/Bibliographic_databasehttp://en.wikipedia.org/wiki/IEEEhttp://en.wikipedia.org/wiki/VLDBhttp://en.wikipedia.org/wiki/Symposium_on_Principles_of_Database_Systemshttp://en.wikipedia.org/wiki/SIGMODhttp://en.wikipedia.org/wiki/Association_for_Computing_Machineryhttp://en.wikipedia.org/wiki/Academic_conferencehttp://en.wikipedia.org/wiki/Data_and_Knowledge_Engineeringhttp://en.wikipedia.org/wiki/ACM_Transactions_on_Database_Systemshttp://en.wikipedia.org/wiki/Academic_journalhttp://en.wikipedia.org/wiki/RAIDhttp://en.wikipedia.org/wiki/Query_optimizationhttp://en.wikipedia.org/wiki/Concurrency_controlhttp://en.wikipedia.org/wiki/Data_modelhttp://en.wikipedia.org/wiki/Prototypehttp://en.wikipedia.org/wiki/Database_theoryhttp://en.wikipedia.org/wiki/IBM_Researchhttp://en.wikipedia.org/wiki/Academiahttp://en.wikipedia.org/wiki/VoltDBhttp://en.wikipedia.org/wiki/NuoDBhttp://en.wikipedia.org/wiki/EnterpriseDBhttp://en.wikipedia.org/wiki/Clustrixhttp://en.wikipedia.org/wiki/Eventual_consistencyhttp://en.wikipedia.org/w/index.php?title=Partition_tolerance&action=edit&redlink=1http://en.wikipedia.org/wiki/Consistency_modelhttp://en.wikipedia.org/wiki/Distributed_computinghttp://en.wikipedia.org/wiki/CAP_theoremhttp://en.wikipedia.org/wiki/Open-source_softwarehttp://en.wikipedia.org/wiki/HBase


10/23



gathering and authorization. Many databases provide active database features in the form of database triggers.

A cloud database relies on cloud technology. Both the database and most of its DBMS resideremotely, "in the cloud", while its applications are both developed by programmers and later maintained and utilized by (application's) end-users through a web browser and Open APIs.

Data warehouses archive data from operational databases and often from external sourcessuch as market research firms. The warehouse becomes the central source of data for use bymanagers 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 touse UPCs so that they can be compared with ACNielsen data. Some basic and essentialcomponents of data warehousing include retrieving, analyzing, and 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, for example byusing the Datalog language.

A distributed database is one in which both the data and the DBMS span multiple computers.

A document-oriented database is designed for storing, retrieving, and managing document-oriented, or semi structured data, information. Document-oriented databases are one of themain categories of NoSQL databases.

An embedded database system is a DBMS which is tightly integrated with an applicationsoftware that requires access to stored data in such a way that the DBMS is hidden from the

applications end-users and requires little or no ongoing maintenance. [22]

End-user databases consist of data developed by individual end-users. Examples of theseare collections of documents, spreadsheets, presentations, multimedia, and other files. Severalproducts 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 (inwhich case it would also be a heterogeneous database system), and provides them with anintegrated conceptual view.
http://en.wikipedia.org/wiki/Heterogeneous_database_systemhttp://en.wikipedia.org/wiki/Federated_database_systemhttp://en.wikipedia.org/wiki/Embedded_databasehttp://en.wikipedia.org/wiki/Distributed_databasehttp://en.wikipedia.org/wiki/Dataloghttp://en.wikipedia.org/wiki/Logic_programminghttp://en.wikipedia.org/wiki/Deductive_databasehttp://en.wikipedia.org/wiki/Data_mininghttp://en.wikipedia.org/wiki/ACNielsenhttp://en.wikipedia.org/wiki/Universal_Product_Codehttp://en.wikipedia.org/wiki/Data_warehousehttp://en.wikipedia.org/wiki/Open_APIhttp://en.wikipedia.org/wiki/Web_browserhttp://en.wikipedia.org/wiki/Cloud_computinghttp://en.wikipedia.org/wiki/Cloud_databasehttp://en.wikipedia.org/wiki/Database_trigger


11/23



Sometimes the term multi-database is used as a synonym to federated database, though itmay 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 isused for distribution, which typically includes an atomic commit protocol (ACP), e.g., the two-phase commit protocol, to allow distributed (global) transactions across the participatingdatabases.

A graph database is a kind of NoSQL database that uses graph structures with nodes, edges,and properties to represent and store information. General graph databases that can store anygraph are distinct from specialized graph databases such as triplestores and networkdatabases.

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 [23][24]) is a special kind of database for knowledge management, providing the means for the computerized collection, organization,and retrieval of knowledge. Also a collection of data representing problems with their solutionsand 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. Theytypically process relatively high volumes of updates using transactions. Examples includecustomer databases that record contact, credit, and demographic information about abusiness' customers, personnel databases that hold information such as salary, benefits, skillsdata about employees, enterprise resource planning systems that record details about product

components, parts inventory, and financial databases that keep track of the organization'smoney, accounting and financial dealings.

A parallel database seeks to improve performance through parallelization for tasks such asloading data, building indexes and evaluating queries.

The major parallel DBMS architectures which are induced by the underlying hardwarearchitecture are:
http://en.wikipedia.org/wiki/Computer_hardwarehttp://en.wikipedia.org/wiki/Parallel_computinghttp://en.wikipedia.org/wiki/Parallel_databasehttp://en.wikipedia.org/wiki/Customer_relationship_managementhttp://en.wikipedia.org/wiki/Transaction_(database)http://en.wikipedia.org/wiki/Operational_databasehttp://en.wikipedia.org/w/index.php?title=Mobile_computing_device&action=edit&redlink=1http://en.wikipedia.org/wiki/Mobile_databasehttp://en.wikipedia.org/wiki/Knowledgehttp://en.wikipedia.org/wiki/Information_retrievalhttp://en.wikipedia.org/wiki/Knowledge_managementhttp://en.wikipedia.org/wiki/Knowledge_basehttp://en.wikipedia.org/wiki/World_Wide_Webhttp://en.wikipedia.org/wiki/Online_encyclopediahttp://en.wikipedia.org/wiki/Hyperlinkhttp://en.wikipedia.org/wiki/Hypermediahttp://en.wikipedia.org/wiki/Hypertexthttp://en.wikipedia.org/wiki/Network_database_modelhttp://en.wikipedia.org/wiki/Triplestorehttp://en.wikipedia.org/wiki/Graph_(data_structure)http://en.wikipedia.org/wiki/Graph_databasehttp://en.wikipedia.org/wiki/Distributed_transactionhttp://en.wikipedia.org/wiki/Two-phase_commit_protocolhttp://en.wikipedia.org/wiki/Middleware_(distributed_applications)


12/23



Shared memory architecture , where multiple processors share the main memoryspace, 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 mainmemory 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 beacted on right away.

A spatial database can store the data with multidimensional features. The queries on such datainclude 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 atemporal version of SQL. More specifically the temporal aspects usually include valid-time andtransaction-time.

A terminology-oriented database builds upon an object-oriented database, often customizedfor 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 includeemail messages, documents, journals, multimedia objects, etc. The name may be misleadingsince some objects can be highly structured. However, the entire possible object collectiondoes not fit into a predefined structured framework. Most established DBMSs now supportunstructured data in various ways, and new dedicated DBMSs are emerging.

Design and modeling

The first task of a database designer is to produce a conceptual data model that reflects the structureof 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 UnifiedModeling Language. A successful data model will accurately reflect the possible state of the externalworld being modeled: for example, if people can have more than one phone number, it will allow thisinformation to be captured. Designing a good conceptual data model requires a good understandingof the application domain; it typically involves asking deep questions about the things of interest to anorganisation, like "can a customer also be a supplier?", or "if a product is sold with two differentforms of packaging, are those the same product or different products?", or "if a plane flies from New
http://en.wikipedia.org/wiki/Unified_Modeling_Languagehttp://en.wikipedia.org/wiki/Conceptual_data_modelhttp://en.wikipedia.org/wiki/Unstructured_datahttp://en.wikipedia.org/wiki/Object-oriented_databasehttp://en.wikipedia.org/wiki/Terminology-oriented_databasehttp://en.wikipedia.org/wiki/Temporal_databasehttp://en.wikipedia.org/wiki/Spatial_databasehttp://en.wikipedia.org/wiki/Real-time_databasehttp://en.wikipedia.org/wiki/Fuzzy_logichttp://en.wikipedia.org/wiki/Probabilistic_databasehttp://en.wikipedia.org/wiki/Shared_nothing_architecturehttp://en.wikipedia.org/wiki/Shared_memory#In_hardware


13/23



York to Dubai via Frankfurt, is that one flight or two (or maybe even three)?". The answers to thesequestions establish definitions of the terminology used for entities (customers, products, flights, flightsegments) and their relationships and attributes.

Producing the conceptual data model sometimes involves input from business processes, or theanalysis of workflow in the organization. This can help to establish what information is needed in thedatabase, and what can be left out. For example, it can help when deciding whether the databaseneeds 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 translatethis into a schema that implements the relevant data structures within the database. This process isoften 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 databasemodel supported by the chosen DBMS. (The terms data model and database model are often usedinterchangeably, but in this article we use data model for the design of a specific database, anddatabase model for the modelling notation used to express that design.)

The most popular database model for general-purpose databases is the relational model, or moreprecisely, the relational model as represented by the SQL language. The process of creating alogical database design using this model uses a methodical approach known as normalization. Thegoal of normalization is to ensure that each elementary "fact" is only recorded in one place, so thatinsertions, 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. This is often called physical database design . A key goal during thisstage is data independence, meaning that the decisions made for performance optimizationpurposes should be invisible to end-users and applications. Physical design is driven mainly by

performance requirements, and requires a good knowledge of the expected workload and accesspatterns, 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 todatabase 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 andfundamentally 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:

Hierarchical database modelNetwork modelRelational modelEntityrelationship model
http://en.wikipedia.org/wiki/Entity%E2%80%93relationship_modelhttp://en.wikipedia.org/wiki/Relational_modelhttp://en.wikipedia.org/wiki/Network_modelhttp://en.wikipedia.org/wiki/Hierarchical_database_modelhttp://en.wikipedia.org/wiki/Datahttp://en.wikipedia.org/wiki/Access_controlhttp://en.wikipedia.org/wiki/Data_independencehttp://en.wikipedia.org/wiki/Database_normalizationhttp://en.wikipedia.org/wiki/Logical_data_modelhttp://en.wikipedia.org/wiki/Database_schemahttp://en.wikipedia.org/wiki/Workflowhttp://en.wikipedia.org/wiki/Business_process_modeling


14/23



Collage of five types of database models.

Enhanced entityrelationship modelObject modelDocument modelEntityattributevalue modelStar schema

An object-relational database combines the two related structures.Physical data models include:

Inverted indexFlat file

Other models include:

Associative model

MultidimensionalmodelMultivalue modelSemantic modelXML databaseNamed graph

External,conceptual, andinternal views

A database managementsystem provides threeviews of the databasedata:

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. [26] Itprovides the synthesis of all the external views. It is out of the scope of the various databaseend-users, and is rather of interest to database application developers and databaseadministrators.The internal level (or physical level ) is the internal organization of data inside a DBMS (seeImplementation section below). It is concerned with cost, performance, scalability and other operational matters. It deals with storage layout of the data, using storage structures such as
http://en.wikipedia.org/wiki/Named_graphhttp://en.wikipedia.org/wiki/XML_databasehttp://en.wikipedia.org/wiki/Semantic_data_modelhttp://en.wikipedia.org/wiki/Multivalue_modelhttp://en.wikipedia.org/wiki/Multidimensional_databasehttp://en.wikipedia.org/wiki/Associative_model_of_datahttp://en.wikipedia.org/wiki/Flat_file_databasehttp://en.wikipedia.org/wiki/Inverted_indexhttp://en.wikipedia.org/wiki/Physical_data_modelhttp://en.wikipedia.org/wiki/Star_schemahttp://en.wikipedia.org/wiki/Entity%E2%80%93attribute%E2%80%93value_modelhttp://en.wikipedia.org/wiki/Enhanced_entity%E2%80%93relationship_modelhttp://en.wikipedia.org/wiki/File:Database_models.jpg


15/23



Traditional view of data[25]

indexes to enhance performance.Occasionally it stores data of individualviews (materialized views), computed fromgeneric data, if performance justificationexists for such redundancy. It balances allthe external views' performancerequirements, possibly conflicting, in anattempt to optimize overall performanceacross 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 externalviews. This allows users to see database information in a more business-related way rather thanfrom a technical, processing viewpoint. For example, a financial department of a company needs thepayment details of all employees as part of the company's expenses, but does not need details aboutemployees that are the interest of the human resources department. Thus different departments needdifferent views of the company's database.

The three-level database architecture relates to the concept of data independence which was one othe major initial driving forces of the relational model. The idea is that changes made at a certainlevel do not affect the view at a higher level. For example, changes in the internal level do not affectapplication programs written using conceptual level interfaces, which reduces the impact of makingphysical changes to improve performance.

The conceptual view provides a level of indirection between internal and external. On one hand itprovides a common view of the database, independent of different external view structures, and onthe other hand it abstracts away details of how the data is stored or managed (internal level). Inprinciple every level, and even every external view, can be presented by a different data model. Inpractice usually a given DBMS uses the same data model for both the external and the conceptuallevels (e.g., relational model). The internal level, which is hidden inside the DBMS and depends on itsimplementation (see Implementation section below), requires a different level of detail and uses itsown 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.[26]

Languages

Database languages are special-purpose languages, which do one or more of the following:

Data definition language defines data types and the relationships among themData manipulation language performs tasks such as inserting, updating, or deleting dataoccurrences
http://en.wikipedia.org/wiki/Data_manipulation_languagehttp://en.wikipedia.org/wiki/Data_definition_languagehttp://en.wikipedia.org/wiki/Human_resourceshttp://en.wikipedia.org/wiki/Materialized_viewhttp://en.wikipedia.org/wiki/Index_(database)http://en.wikipedia.org/wiki/File:Traditional_View_of_Data_SVG.svg


16/23



Query language 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. Itwas one of the first commercial languages for the relational model, although it departs in somerespects from the relational model as described by Codd (for example, the rows and columnsof a table can be ordered). SQL became a standard of the American National StandardsInstitute (ANSI) in 1986, and of the International Organization for Standardization (ISO) in 1987The standards have been regularly enhanced since and is supported (with varying degrees of

conformance) by all mainstream commercial relational DBMSs. [27][28]

OQL is an object model language standard (from the Object Data Management Group). It hasinfluenced the design of some of the newer query languages like JDOQL and EJB QL.

XQuery is a standard XML query language implemented by XML database systems such asMarkLogic and eXist, by relational databases with XML capability such as Oracle and DB2,and also by in-memory XML processors such as Saxon.

SQL/XML combines XQuery with SQL.[29]

A database language may also incorporate features like:

DBMS-specific Configuration and storage engine managementComputations to modify query results, like counting, summing, averaging, sorting, grouping,and cross-referencingConstraint 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

Performance, security, and availability

Because of the critical importance of database technology to the smooth running of an enterprise,database systems include complex mechanisms to deliver the required performance, security, andavailability, and allow database administrators to control the use of these features.

Storage

Database storage is the container of the physical materialization of a database. It comprises theinternal (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 anexternal level from the internal level when needed. Putting data into permanent storage is generallythe responsibility of the database engine a.k.a. "storage engine". Though typically accessed by a
http://en.wikipedia.org/wiki/Database_enginehttp://en.wikipedia.org/wiki/Data_structurehttp://en.wikipedia.org/wiki/Metadatahttp://en.wikipedia.org/wiki/XQueryhttp://en.wikipedia.org/wiki/SQL/XMLhttp://en.wikipedia.org/wiki/Saxon_XSLThttp://en.wikipedia.org/wiki/EXisthttp://en.wikipedia.org/wiki/MarkLogichttp://en.wikipedia.org/wiki/XQueryhttp://en.wikipedia.org/wiki/EJB_QLhttp://en.wikipedia.org/w/index.php?title=JDOQL&action=edit&redlink=1http://en.wikipedia.org/wiki/Object_Data_Management_Grouphttp://en.wikipedia.org/wiki/OQLhttp://en.wikipedia.org/wiki/International_Organization_for_Standardizationhttp://en.wikipedia.org/wiki/American_National_Standards_Institutehttp://en.wikipedia.org/wiki/Codd%27s_12_ruleshttp://en.wikipedia.org/wiki/Query_language


17/23



DBMS through the underlying operating system (and often utilizing the operating systems' filesystems as intermediates for storage layout), storage properties and configuration setting areextremely important for the efficient operation of the DBMS, and thus are closely maintained bydatabase administrators. A DBMS, while in operation, always has its database residing in severaltypes of storage (e.g., memory and external storage). The database data and the additional neededinformation, possibly in very large amounts, are coded into bits. Data typically reside in the storage instructures that look completely different from the way the data look in the conceptual and externallevels, but in ways that attempt to optimize (the best possible) these levels' reconstruction whenneeded by users and programs, as well as for computing additional types of needed information fromthe data (e.g., when querying the database).

Some DBMSs support specifying which character encoding was used to store data, so multipleencodings can be used in the same database.

Various low-level database storage structures are used by the storage engine to serialize the datamodel so it can be written to the medium of choice. Techniques such as indexing may be used toimprove performance. Conventional storage is row-oriented, but there are also column-oriented andcorrelation databases.

Materialized views

Often storage redundancy is employed to increase performance. A common example is storingmaterialized views , which consist of frequently needed external views or query results. Storing suchviews 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 withtheir 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 multipleend-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 objectcopies. In many cases the entire database is replicated.

Security

Database security deals with all various aspects of protecting the database content, its owners, andits users. It ranges from protection from intentional unauthorized database uses to unintentionaldatabase 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) isallowed to access what information in the database. The information may comprise specificdatabase objects (e.g., record types, specific records, data structures), certain computations over certain objects (e.g., query types, or specific queries), or utilizing specific access paths to the former
http://en.wikipedia.org/wiki/Database_securityhttp://en.wikipedia.org/wiki/Correlation_databasehttp://en.wikipedia.org/wiki/Column-oriented_DBMShttp://en.wikipedia.org/wiki/Database_storage_structureshttp://en.wikipedia.org/wiki/Character_encodinghttp://en.wikipedia.org/wiki/File_system


18/23



(e.g., using specific indexes or other data structures to access information). Database accesscontrols are set by special authorized (by the database owner) personnel that uses dedicatedprotected security DBMS interfaces.

This may be managed directly on an individual basis, or by the assignment of individuals andprivileges to groups, or (in the most elaborate models) through the assignment of individuals andgroups to roles which are then granted entitlements. Data security prevents unauthorized users fromviewing or updating the database. Using passwords, users are allowed access to the entiredatabase or subsets of it called "subschemas". For example, an employee database can contain allthe data about an individual employee, but one group of users may be authorized to view only payrolldata, while others are allowed access to only work history and medical data. If the DBMS provides away 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., fromcorruption, 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 itwas 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 changesrather than leaving this to the database. Monitoring can be set up to attempt to detect securitybreaches.

Transactions and concurrency

Database transactions can be used to introduce some level of fault tolerance and data integrity after

recovery from a 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 lock, etc.), anabstraction supported in database and also other systems. Each transaction has well definedboundaries in terms of which program/code executions are included in that transaction (determinedby the transaction's programmer via special transaction commands).

The acronym ACID describes some ideal properties of a database transaction: Atomicity,Consistency, Isolation, and Durability.

Migration

See also section Database migration in article Data migration

A database built with one DBMS is not portable to another DBMS (i.e., the other DBMS cannot runit). However, in some situations it is desirable to move, migrate a database from one DBMS toanother. The reasons are primarily economical (different DBMSs may have different 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. Thetransformation should maintain (if possible) the database related application (i.e., all relatedapplication programs) intact. Thus, the database's conceptual and external architectural levels should
http://en.wikipedia.org/wiki/Total_cost_of_ownershiphttp://en.wikipedia.org/wiki/Data_migrationhttp://en.wikipedia.org/wiki/Data_migration#Database_migrationhttp://en.wikipedia.org/wiki/Durability_(database_systems)http://en.wikipedia.org/wiki/Isolation_(database_systems)http://en.wikipedia.org/wiki/Consistency_(database_systems)http://en.wikipedia.org/wiki/Atomicity_(database_systems)http://en.wikipedia.org/wiki/ACIDhttp://en.wikipedia.org/wiki/Lock_(database)http://en.wikipedia.org/wiki/Crash_(computing)http://en.wikipedia.org/wiki/Data_integrityhttp://en.wikipedia.org/wiki/Fault_tolerancehttp://en.wikipedia.org/wiki/Database_transactionshttp://en.wikipedia.org/wiki/Database_audithttp://en.wikipedia.org/wiki/Data_encryptionhttp://en.wikipedia.org/wiki/Physical_securityhttp://en.wikipedia.org/wiki/Data_securityhttp://en.wikipedia.org/wiki/Privilege_(Computing)


19/23



be maintained in the transformation. It may be desired that also some aspects of the architectureinternal level are maintained. A complex or large database migration may be a complicated andcostly (one-time) project by itself, which should be factored into the decision to migrate. This in spiteof 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 anappropriate general-purpose DBMS can be selected to be utilized for this purpose. A DBMSprovides the needed user interfaces to be utilized by database administrators to define the neededapplication's data structures within the DBMS's respective data model. Other user interfaces areused 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 istypically populated with initial application's data (database initialization, which is typically a distinctproject; in many cases using specialized DBMS interfaces that support bulk insertion) before makingit operational. In some cases the database becomes operational while empty of application data,and data is accumulated during its operation.

After the database is created, initialised and populated it needs to be maintained. Various databaseparameters may need changing and the database may need to be tuned (tuning) for better performance; application's data structures may be changed or added, new related applicationprograms 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., caseswhen the database is found corrupted due to a software error, or if it has been updated witherroneous data). To achieve this a backup operation is done occasionally or continuously, whereeach desired database state (i.e., the values of its data and their embedding in database's datastructures) is kept within dedicated backup files (many techniques exist to do this effectively). Whenthis state is needed, i.e., when it is decided by a database administrator to bring the database backto this state (e.g., by specifying this state by a desired point in time when the database was in thisstate), these files are utilized to restore that state.

Other

Other DBMS features might include:

Database logsGraphics component for producing graphs and charts, especially in a data warehouse systemQuery optimizer Performs query optimization on every query to choose for it the mostefficient query plan (a partial order (tree) of operations) to be executed to compute the queryresult. May be specific to a particular storage engine.Tools or hooks for database design, application programming, application program
http://en.wikipedia.org/wiki/Query_planhttp://en.wikipedia.org/wiki/Query_optimizationhttp://en.wikipedia.org/wiki/Query_optimizerhttp://en.wikipedia.org/wiki/Database_loghttp://en.wikipedia.org/wiki/Database_tuninghttp://en.wikipedia.org/wiki/User_interfacehttp://en.wikipedia.org/wiki/General-purpose_DBMS


20/23



maintenance, database performance analysis and monitoring, database configurationmonitoring, DBMS hardware configuration (a DBMS and related database may spancomputers, networks, and storage units) and related database mapping (especially for adistr ibuted DBMS), storage allocation and database layout monitoring, storage migration, etc.

See a lso

Refer e nces

Comparison of database toolsComparison of object database management systemsComparison of object-relational database management systemsComparison of relational database management systemsData accessData hierarchyData storeData warehouseDatabase testingDatabase-centric architectureMetadataQuestion-focused dataset

1. ^ Jef frey Ullman 1997: First course in database systems , PrenticeHall Inc., Simon & Schuster, Page 1,ISBN 0-13-861337-0.

2. ^ Tsitchizris, D. C. and F. H. Lochovsky (1982). Data Models. Englewood-Cliffs, PrenticeHall.3. ^ Beynon-Davies P. (2004). Database Systems 3rd Edition. Palgrave, Basingstoke, UK. ISBN 1-4039-

1601-24. ^ Raul F. Chong, Michael Dang, Dwaine R. Snow, Xiaomei Wang (3 July 2008). "Introduction to DB2"

(http://www.ibmpressbooks.com/articles/article.asp?p=1163083). Retrieved 17 March 2013.. This articlequotes a development time of 5 years involving 750 people for DB2 release 9 alone

5. ^ C. W. Bachmann (November 1973), "The Programmer as Navigator"(http://www.cs.uiuc.edu/class/fa05/cs511/Spring05/other_papers/p653-bachman.pdf), CACM (Turing

Award Lecture 1973)6. ^ "database, n" (http://www.oed.com/view/Entry/47411). OED Online . Oxford University Press. June

2013. Retrieved July 12, 2013.7. ^ IBM Corporation. "IBM Information Management System (IMS) 13 Transaction and Database Servers

delivers high performance and low total cost of ownership" (http://www-01.ibm.com/common/ssi/cgi-

bin/ssialias?subt e=ca&infot e=an&a name=iSource&su lier=897&letternum=ENUS213-381 .
http://www-01.ibm.com/common/ssi/cgi-bin/ssialias?subtype=ca&infotype=an&appname=iSource&supplier=897&letternum=ENUS213-381http://www.oed.com/view/Entry/47411http://www.cs.uiuc.edu/class/fa05/cs511/Spring05/other_papers/p653-bachman.pdfhttp://www.ibmpressbooks.com/articles/article.asp?p=1163083http://en.wikipedia.org/wiki/Special:BookSources/1403916012http://en.wikipedia.org/wiki/Special:BookSources/0138613370http://en.wikipedia.org/wiki/Jeffrey_Ullmanhttp://en.wikipedia.org/wiki/Question-focused_datasethttp://en.wikipedia.org/wiki/Database-centric_architecturehttp://en.wikipedia.org/wiki/Database_testinghttp://en.wikipedia.org/wiki/Data_storehttp://en.wikipedia.org/wiki/Data_hierarchyhttp://en.wikipedia.org/wiki/Data_accesshttp://en.wikipedia.org/wiki/Comparison_of_relational_database_management_systemshttp://en.wikipedia.org/wiki/Comparison_of_object-relational_database_management_systemshttp://en.wikipedia.org/wiki/Comparison_of_object_database_management_systemshttp://en.wikipedia.org/wiki/Comparison_of_database_tools


21/23



Retr ieved Feb 20, 2014.8. ^ Codd, E.F. (1970)."A Relational Model of Data for Large Shared Data Banks"

(http://www.seas.upenn.edu/~zives/03f/cis550/codd.pdf). In: Communications of the ACM 13 (6): 377387.

9. ^ William Hershey and Carol Easthope, "A set theoretic data structure and retrieval language"(https://docs.google.com/open?id=0B4t_NX-

QeWDYNmVhYjAwMWMtYzc3ZS00YjI0LWJhMjgtZTYyODZmNmFkNThh), Spring Joint Computer Conf erence, May 1972 in ACM SIGIR Forum , Volume 7, Issue 4 (December 1972), pp. 4555,DOI=10.1145/1095495.1095500 (http://doi.acm.org/10.1145/1095495.1095500)

10. ^ Ken North, "Sets, Data Models and Data Independence"(http://drdobbs.com/blogs/database/228700616), Dr. Dobb's , 10 March 2010

11. ^ De scription of a set-theoretic data structure (http://hdl.handle.net/2027.42/4163), D. L. Childs, 1968,Tec hnical Report 3 of the CONCOMP (Research in Conversational Use of Computers) Project,University of Michigan, Ann Arbor, Michigan, USA

12. ^ F e asibility of a Set-Theoretic Data Structure : A General Structure Based on a Reconstituted

Def i nition of Relation (http://hdl.handle.net/2027.42/4164), D. L. Childs, 1968, Technical Report 6 of theCONCOMP (Research in Conversational Use of Computers) Project, University of Michigan, Ann Arbor,Michigan, USA

13. ^ M I CRO Information Management System (Version 5.0) Reference Manual (http://docs.google.com/viewer?a=v&pid=explorer&chrome=true&srcid=0B4t_NX-QeWDYZGMwOTRmOTItZTg2Zi00YmJkLTg4MTktN2E4MWU0YmZlMjE3), M.A. Kahn, D.L. Rumelhand B.L. Bronson, October 1977, Institute of Labor and Industrial Relations (ILIR), University of Michigan and Wayne State University

14. ^ Interview with Wayne Ratliff (http://www.foxprohistory.org/interview_wayne_ratliff.htm). The FoxProHistory. Retrieved on 2013-07-12.

15. ^ Development of an object-oriented DBMS; Portland, Oregon, United States; Pages: 472 482; 1986;ISBN 0-89791-204-7

16. ^ "Clusterpoint XML database" (http://www.clusterpoint.com). 28 Mar 2014.17. ^ "MarkLogic NoSQL database" (http://www.marklogic.com). 28 Mar 2014.18. ^ "Oracle XML DB database" (http://www.oracle.com/technetwork/database/database-

technologies/xmldb/overview/index.html). 28 Mar 2014.19. ^ "DB-Engines Ranking" (http://db-engines.com/en/ranking). January 2013. Retrieved 22 January 2013.

20. ^ Pr octor, Seth (2013). "Exploring the Architecture of the NuoDB Database, Part 1"(http://www.infoq.com/articles/nuodb-architecture-1/). Retrieved 2013-07-12.21. ^ "TeleCommunication Systems Signs up as a Reseller of TimesTen; Mobile Operators and Carriers

Gain Real-Time Platform for Location-Based Services"(http://findarticles.com/p/articles/mi_m0EIN/is_2002_June_24/ai_87694370). Business Wire . 2002-06-24.

22. ^ Gr aves, Steve. "COTS Databases For Embedded Systems" (http://www.embedded-computing.com/articles/id/?2020), Embedded Computing Design magazine, January 2007. Retrieved on

August 13, 2008.
http://www-01.ibm.com/common/ssi/cgi-bin/ssialias?subtype=ca&infotype=an&appname=iSource&supplier=897&letternum=ENUS213-381http://www.embedded-computing.com/articles/id/?2020http://findarticles.com/p/articles/mi_m0EIN/is_2002_June_24/ai_87694370http://www.infoq.com/articles/nuodb-architecture-1/http://db-engines.com/en/rankinghttp://www.oracle.com/technetwork/database/database-technologies/xmldb/overview/index.htmlhttp://www.marklogic.com/http://www.clusterpoint.com/http://en.wikipedia.org/wiki/Special:BookSources/0897912047http://www.foxprohistory.org/interview_wayne_ratliff.htmhttp://docs.google.com/viewer?a=v&pid=explorer&chrome=true&srcid=0B4t_NX-QeWDYZGMwOTRmOTItZTg2Zi00YmJkLTg4MTktN2E4MWU0YmZlMjE3http://hdl.handle.net/2027.42/4164http://hdl.handle.net/2027.42/4163http://drdobbs.com/blogs/database/228700616http://doi.acm.org/10.1145/1095495.1095500https://docs.google.com/open?id=0B4t_NX-QeWDYNmVhYjAwMWMtYzc3ZS00YjI0LWJhMjgtZTYyODZmNmFkNThhhttp://www.seas.upenn.edu/~zives/03f/cis550/codd.pdfhttp://www-01.ibm.com/common/ssi/cgi-bin/ssialias?subtype=ca&infotype=an&appname=iSource&supplier=897&letternum=ENUS213-381


22/23



Furth e r reading

Exter n al links

Database (http://www.dmoz.org/Computers/Data_Formats/Database) at DMOZ

. , .24. ^ "OWL DL Semantics" (http://www.obitko.com/tutorials/ontologies-semantic-web/owl-dl-semantics.htm

Retr ieved 10 December 2010.25. ^ itl.nist.gov (1993) Integration Definition for Information Modeling (IDEFIX)

(http://www.itl.nist.gov/fipspubs/idef1x.doc). 21 December 1993.

26. ^ a b Date 1990, pp. 313227. ^ Chapple, Mike. "SQL Fundamentals" (http://databases.about.com/od/sql/a/sqlfundamentals.htm).

Dat a bases . About.com. Retrieved 2009-01-28.28. ^ "Str uctured Query Language (SQL)" (http://publib.boulder.ibm.com/infocenter/db2luw/v9/index.jsp?

topic=com.ibm.db2.udb.admin.doc/doc/c0004100.htm). International Business Machines. October 27,2006. Retrieved 2007-06-10.

29. ^ Wagner, Michael (2010), "1. Auflage", SQL/XML:2006 Evaluierung der Standardkonformitt aus g ewhlter Datenbanksysteme , Diplomica Verlag, ISBN 3-8366-9609-6

Ling Liu and Tamer M. zsu (Eds.) (2009). "Encyclopedia of Database Systems(http://www.springer.com/computer/database+management+&+information+retrieval/book/978-0-387-49616-0), 4100 p. 60 illus. ISBN 978-0-387-49616-0.Beynon-Davies, P. (2004). Database Systems. 3rd Edition. Palgrave, Houndmills, Basingstoke.Connolly, Thomas and Carolyn Begg. Database Systems. New York: Harlow, 2002.Date, C. J. (2003). An Introduction to Database Systems, Fifth Edition . Addison Wesley. ISBN 0-201-51381-1.Gray, J. and Reuter, A. Transaction Processing: Concepts and Techniques , 1st edition, MorganKauf mann 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(htt p : //pages.cs.wisc.edu/~dbbook/)

Abr aham Silberschatz, Henry F. Korth, S. Sudarshan, Database System Concepts (http://www.db-boo k .com/)

Discussion on database systems, [1] (http://www.bbconsult.co.uk/Documents/Database-Systems.docx)Lightstone, S.; Teorey, T.; Nadeau, T. (2007). Physical Database Design: the database professional'sgui d e to exploiting indexes, views, storage, and more . Morgan Kaufmann Press. ISBN 0-12-369389-6.Teo r ey, T.; Lightstone, S. and Nadeau, T. Database Modeling & Design: Logical Design , 4th edition,Morgan Kaufmann Press, 2005. ISBN 0-12-685352-5
http://en.wikipedia.org/wiki/Special:BookSources/0126853525http://en.wikipedia.org/wiki/Special:BookSources/0-12-369389-6http://en.wikipedia.org/wiki/International_Standard_Book_Numberhttp://www.bbconsult.co.uk/Documents/Database-Systems.docxhttp://www.db-book.com/http://en.wikipedia.org/wiki/Abraham_Silberschatzhttp://pages.cs.wisc.edu/~dbbook/http://en.wikipedia.org/wiki/Johannes_Gehrkehttp://en.wikipedia.org/wiki/Raghu_Ramakrishnanhttp://en.wikipedia.org/wiki/Special:BookSources/0-201-51381-1http://en.wikipedia.org/wiki/International_Standard_Book_Numberhttp://en.wikipedia.org/wiki/Christopher_J._Datehttp://en.wikipedia.org/wiki/Special:BookSources/9780387496160http://www.springer.com/computer/database+management+&+information+retrieval/book/978-0-387-49616-0http://en.wikipedia.org/wiki/Special:BookSources/3-8366-9609-6http://en.wikipedia.org/wiki/International_Standard_Book_Numberhttp://publib.boulder.ibm.com/infocenter/db2luw/v9/index.jsp?topic=com.ibm.db2.udb.admin.doc/doc/c0004100.htmhttp://databases.about.com/od/sql/a/sqlfundamentals.htmhttp://www.itl.nist.gov/fipspubs/idef1x.dochttp://www.obitko.com/tutorials/ontologies-semantic-web/owl-dl-semantics.htmlhttp://en.wikipedia.org/wiki/DMOZhttp://www.dmoz.org/Computers/Data_Formats/Database


23/23


Retrieved from "http://en.wikipedia.org/w/index.php?title=Database&oldid=612977212"Categories: Database management systems Databases Database theory

This page was last modified on 15 June 2014 at 06:02.Text is available under the Creative Commons Attribution-ShareAlike License; additional termsmay apply. By using this site, you agree to the Terms of Use and Privacy Policy. Wikipedia isa registered trademark of the Wikimedia Foundation, Inc., a non-profit organization.
http://www.wikimediafoundation.org/http://wikimediafoundation.org/wiki/Privacy_policyhttp://wikimediafoundation.org/wiki/Terms_of_Usehttp://en.wikipedia.org/wiki/Wikipedia:Text_of_Creative_Commons_Attribution-ShareAlike_3.0_Unported_Licensehttp://en.wikipedia.org/wiki/Help:Categoryhttp://en.wikipedia.org/w/index.php?title=Database&oldid=612977212http://en.wikipedia.org/wiki/Category:Database_theoryhttp://en.wikipedia.org/wiki/Category:Databaseshttp://en.wikipedia.org/wiki/Category:Database_management_systems