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GraphQL is a data query and manipulation language for APIs that allows a client to specify what data it needs ("declarative data fetching"). A GraphQL server can fetch data from separate sources for a single client query and present the results in a unified graph . [ 2 ]
Gremlin is an Apache2-licensed graph traversal language that can be used by graph system vendors. There are typically two types of graph system vendors: OLTP graph databases and OLAP graph processors.
In September 2019 a proposal for a project to create a new standard graph query language (ISO/IEC 39075 Information Technology — Database Languages — GQL) [3] was approved by a vote of national standards bodies which are members of ISO/IEC Joint Technical Committee 1(ISO/IEC JTC 1).
GraphQL: an open-source data query and manipulation language for APIs. Dgraph implements modified GraphQL language called DQL (formerly GraphQL+-) Gremlin: a graph programming language that is a part of Apache TinkerPop open-source project [46] SPARQL: a query language for RDF databases that can retrieve and manipulate data stored in RDF format
There are two graph models in current use: the Resource Description Framework (RDF) model and the Property Graph model. The RDF model has been standardized by W3C in a number of specifications. The Property Graph model, on the other hand, has a multitude of implementations in graph databases, graph algorithms, and graph processing facilities.
GQL may refer to: . Google Query Language, SQL-like language for retrieving entities and keys in Google Cloud Datastore; Graph Query Language, an international standard property graph query language
Microsoft Excel is a spreadsheet editor developed by Microsoft for Windows, macOS, Android, iOS and iPadOS.It features calculation or computation capabilities, graphing tools, pivot tables, and a macro programming language called Visual Basic for Applications (VBA).
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.