145:" approach of knitting together multiple database products, each handing a different model, to achieve a multi-model capability as described by Martin Fowler. 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, so multi-model databases have begun to fill in this gap.
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must be able to synchronize updates across multiple keys. ACID transactions, if they are sufficiently performant, allow such synchronization. JSON documents, graphs, and relational tables can all be implemented in a manner that inherits the horizontal scalability and fault-tolerance of the underlying data store.
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In addition to offering multiple data models in a single data store, some databases allow developers to easily define custom data models. This capability is enabled by ACID transactions with high performance and scalability. In order for a custom data model to support concurrent updates, the database
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As more and more platforms are proposed to deal with multi-model data, there are a few works on benchmarking multi-model databases. For instance, Pluciennik, Oliveira, and UniBench reviewed existing multi-model databases and made an evaluation effort towards comparing multi-model databases and other
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in the early 1990s and in a more broader scope even to federated and integrated DBMSs in the early 1980s. An ORDBMS system manages different types of data such as relational, object, text and spatial by plugging domain specific data types, functions and index implementations into the DBMS kernels. A
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The main difference between the available multi-model databases is related to their architectures. Multi-model databases can support different models either within the engine or via different layers on top of the engine. Some products may provide an engine which supports documents and graphs while
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models that are non-relational, including documents, triples, key–value stores and graphs are popular. Arguably, geospatial data, temporal data, and text data are also separate models, though indexed, queryable text data is generally termed a
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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.
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they can employ a unified query language such as AQL, Orient SQL, SQL/XML, SQL/JSON to retrieve correlated multi-model data, such as graph-JSON-key/value, XML-relational, and JSON-relational in a single
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against a single, integrated backend. In contrast, most database management systems are organized around a single data model that determines how data can be organized, stored, and manipulated.
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A multi-model database is a database that can store, index and query data in more than one model. For some time, databases have primarily supported only one model, such as:
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For some time, it was all but forgotten (or considered irrelevant) that there were any other database models besides relational. The relational model and notion of
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SQL and NoSQL databases respectively. They pointed out that the advantages of multi-model databases over single-model databases are as follows :
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they are able to ingest a variety of data formats such as CSV (including Graph, Relational), JSON into storage without any additional efforts.
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Fábio
Roberto Oliveira, Luis del Val Cura. "Performance Evaluation of NoSQL Multi-Model Data Stores in Polyglot Persistence Applications".
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were the default standard for all data storage. However, prior to the dominance of relational data modeling, from about 1980 to 2005, the
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The first time the word "multi-model" has been associated to the databases was on May 30, 2012 in
Cologne, Germany, during the
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others provide layers on top of a key-key store. With a layered architecture, each data model is provided via its own
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databases became prominent after 2009. NoSQL databases use a variety of data models, with
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models are examples of data models that may be supported by a multi-model database.
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ODBMS, "On Multi-Model
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they are able to support multi-model ACID transactions in the stand-alone mode.
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Pluciennik and Kamil Zgorzalek. "The Multi-model Databases - A Review".
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The 451 Group, "Neither Fish Nor Fowl: The Rise of Multi-Model
Databases"
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The 451 Group, "Neither Fish Nor Fowl: The Rise of Multi-Model
Databases"
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multi-model database is most directly a response to the "
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The idea of multi-model databases can be traced back to
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51:Background
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