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Most database management systems are organized around a single data model that determines how data can be organized, stored, and manipulated. In contrast, a multi-model database is designed to support multiple data models against a single, integrated backend.〔(The 451 Group, "Neither Fish Nor Fowl: The Rise of Multi-Model Databases" )〕 Document, graph, relational, and key-value models are examples of data models that may be supported by a multi-model database. == Background == The relational data model became popular after its publication by Edgar F. Codd in 1970. Due to increasing requirements for horizontal scalability and fault tolerance, NoSQL databases became prominent after 2009. NoSQL databases use a variety of data models, with document, graph, and key-value models being popular.〔(Infoworld, "The Rise of the Multi-Model Database" )〕 Enterprises and applications that require multiple data models sometimes adopt a strategy of polyglot persistence,〔(Polyglot Persistence )〕 using separate data stores for each model. This strategy has two major disadvantages: it leads to a significant increase in operational complexity, and there is no support for maintaining data consistency across the separate data stores. Multi-model databases are intended to offer the data modeling advantages of polyglot persistence without its disadvantages. Operational complexity, in particular, is reduced through the use of a single data store.〔 The first multi-model database was OrientDB, created in 2010 as an answer to the fragmented NoSQL environment, with the goal of providing one product to replace multiple NoSQL databases. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Multi-model database」の詳細全文を読む スポンサード リンク
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