Editing Database (section)

==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 trigger]]s.
* 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 API]]s.
* [[Data warehouse]]s{{citation needed|date=December 2022|reason=Data warehouses usually aren't classified as a type of database.}} 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]] 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.<ref>Graves, Steve. [http://www.embedded-computing.com/articles/id/?2020 "COTS Databases For Embedded Systems"] {{Webarchive|url=https://web.archive.org/web/20071114050734/http://www.embedded-computing.com/articles/id/?2020 |date=2007-11-14 }}, ''Embedded Computing Design'' magazine, January 2007. Retrieved on August 13, 2008.</ref>
*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{{which|date=December 2022}} exist to support such databases.
* 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 for 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 [[triplestore]]s 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 [[hyperlink]]ed to that object. Hypertext databases are particularly useful for organizing large amounts of disparate information. For example, they are useful for organizing [[online encyclopedia]]s, 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<ref>Argumentation in Artificial Intelligence by Iyad Rahwan, Guillermo R. Simari</ref><ref>{{cite web
| title = OWL DL Semantics
| url = http://www.obitko.com/tutorials/ontologies-semantic-web/owl-dl-semantics.html
| access-date = 10 December 2010}}</ref>) 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 database]]s 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 database]]s employ [[fuzzy logic]] to draw inferences from imprecise data.
* [[Real-time database]]s 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]]. 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.<!-- Isn't this a document-oriented database? If not, clearly distinguish. -->