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  2. GraphQL - Wikipedia

    en.wikipedia.org/wiki/GraphQL

    GraphQL is a data query and manipulation language that allows specifying what data is to be retrieved ("declarative data fetching") or modified. A GraphQL server can process a client query using data from separate sources and present the results in a unified graph. [2] The language is not tied to any specific database or storage engine.

  3. Open Data Protocol - Wikipedia

    en.wikipedia.org/wiki/Open_Data_Protocol

    The OData protocol specifies various 'system query options' endpoints should accept, these can be used to filter, order, map or paginate data. Query options can be appended to a URL after a ? character and are separated by & characters; each option consists of a $ -sign prefixed name and its value, separated by a = sign, for example: OData ...

  4. Graph Query Language - Wikipedia

    en.wikipedia.org/wiki/Graph_Query_Language

    This query would return the city of residence of each person in the graph with residential information, and, if an EU national, which country they come from. Queries are therefore able to first project a sub-graph of the graph input into the query, and then extract the data values associated with that subgraph.

  5. Cypher (query language) - Wikipedia

    en.wikipedia.org/wiki/Cypher_(query_language)

    Cypher is a declarative graph query language that allows for expressive and efficient data querying in a property graph. [1]Cypher was largely an invention of Andrés Taylor while working for Neo4j, Inc. (formerly Neo Technology) in 2011. [2]

  6. Query language - Wikipedia

    en.wikipedia.org/wiki/Query_language

    Broadly, query languages can be classified according to whether they are database query languages or information retrieval query languages. The difference is that a database query language attempts to give factual answers to factual questions, while an information retrieval query language attempts to find documents containing information that is relevant to an area of inquiry.

  7. Online analytical processing - Wikipedia

    en.wikipedia.org/wiki/Online_analytical_processing

    In computing, online analytical processing, or OLAP (/ ˈ oʊ l æ p /), is an approach to quickly answer multi-dimensional analytical (MDA) queries. [1] The term OLAP was created as a slight modification of the traditional database term online transaction processing (OLTP). [2]

  8. Gremlin (query language) - Wikipedia

    en.wikipedia.org/wiki/Gremlin_(query_language)

    These steps are sufficient to provide general purpose computing and what is typically required to express the common motifs of any graph traversal query. Given that Gremlin is a language, an instruction set, and a virtual machine, it is possible to design another traversal language that compiles to the Gremlin traversal machine (analogous to ...

  9. Semantic query - Wikipedia

    en.wikipedia.org/wiki/Semantic_Query

    Semantic queries work on named graphs, linked data or triples. This enables the query to process the actual relationships between information and infer the answers from the network of data. This is in contrast to semantic search, which uses semantics (meaning of language constructs) in unstructured text to produce a better search result.