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Graph databases are commonly referred to as a NoSQL database. Graph databases are similar to 1970s network model databases in that both represent general graphs, but network-model databases operate at a lower level of abstraction [3] and lack easy traversal over a chain of edges. [4] The underlying storage mechanism of graph databases can vary.
Cypher was originally intended to be used with the graph database Neo4j, but was opened up through the openCypher project in October 2015. [ 3 ] The language was designed with the power and capability of SQL (standard query language for the relational database model ) in mind, but Cypher was based on the components and needs of a database built ...
Neo4j is a graph database management system (GDBMS) developed by Neo4j Inc. The data elements Neo4j stores are nodes , edges connecting them, and attributes of nodes and edges.
OrientDB is an open source NoSQL database management system written in Java. It is a Multi-model database, supporting graph, document and object models, [2] the relationships are managed as in graph databases with direct connections between records. It supports schema-less, schema-full and schema-mixed modes.
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.
Graph databases, which store information in nodes and relationships instead of tables like Excel sheets, have grown in popularity amid an explosion of data across industries.
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. The table below outlines those graph vendors that support Gremlin.
The popularization of knowledge graphs and their accompanying methods have led to the development of graph databases such as Neo4j [22] and GraphDB. [23] These graph databases allow users to easily store data as entities and their interrelationships, and facilitate operations such as data reasoning, node embedding, and ontology development on ...