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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 ...
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.
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 ...
NoSQL (originally referring to "non-SQL" or "non-relational") [1] is an approach to database design that focuses on providing a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases. Instead of the typical tabular structure of a relational database, NoSQL databases ...
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.
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 ...
This is a comparison of notable object database management systems, showing what fundamental object database features are implemented natively. Name
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 ...