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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 ...
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.
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 ...
SPARQL is an extension of RDQL that supports extraction of RDF subgraphs. In 2008, SPARQL 1.0 became a W3C recommendation [8] and SPARQL 1.1 became a W3C recommendation in 2013. [9] The RQL family of languages includes RQL, SeRQL, and eRQL. [5] These languages support querying of both data and schema.
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.
List of SPARQL implementations available for querying and manipulating RDF data.
Table compares implementations of block ciphers. Block ciphers are defined as being deterministic and operating on a set number of bits (termed a block) using a symmetric key. Each block cipher can be broken up into the possible key sizes and block cipher modes it can be run with.
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]