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SPARQL (pronounced "sparkle", a recursive acronym [2] for SPARQL Protocol and RDF Query Language) is an RDF query language—that is, a semantic query language for databases—able to retrieve and manipulate data stored in Resource Description Framework (RDF) format.
G-CORE is a research language designed by a group of academic and industrial researchers and language designers which draws on features of Cypher, PGQL and SPARQL. [ 37 ] [ 38 ] The project was conducted under the auspices of the Linked Data Benchmark Council (LDBC), starting with the formation of a Graph Query Language task force in late 2015 ...
The Cypher query language depicts patterns of nodes and relationships and filters those patterns based on labels and properties. Cypher’s syntax is based on ASCII art, which is text-based visual art for computers. This makes the language very visual and easy to read because it both visually and structurally represents the data specified in ...
Graph query languages, such as Cypher Query Language, GraphQL, and Gremlin, are designed to query graph databases, of which RDF data stores are an example. [13] The Topic Map Query Language (TMQL) [14] is a query language for topic maps, a data representation similar to but more general than RDF.
Cypher is a query language for the Neo4j graph database; DMX is a query language for data mining models; Datalog is a query language for deductive databases; F-logic is a declarative object-oriented language for deductive databases and knowledge representation. FQL enables you to use a SQL-style interface to query the data exposed by the Graph API.
AnzoGraph DB is a massively parallel native Graph Online Analytics Processing style database built to support SPARQL and Cypher Query Language to analyze trillions of relationships. AnzoGraph DB is designed for interactive analysis of large sets of semantic triple data, but also supports labeled properties under proposed W3C standards.
List of SPARQL implementations available for querying and manipulating RDF data.
It is used for embedded analytics that require graph algorithms, graph views, named queries, aggregates, geospatial, built-in data science functions, data warehouse-style BI and reporting functions. It allows users to load and query RDF data using SPARQL or Cypher for OLAP-style analytics. [12] [13]