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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 ...
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 ...
C++, Go, Java, Python: A scalable open-source distributed graph database for storing and handling billions of vertices and trillions of edges with milliseconds of latency. It is designed based on a shared-nothing distributed architecture for linear scalability. [37] Neo4j: 2025.01.0: 2025-02-06 [38]
Cypher [28] is a language originally designed by Andrés Taylor and colleagues at Neo4j Inc., and first implemented by that company in 2011. Since 2015 it has been made available as an open source language description [ 29 ] with grammar tooling, a JVM front-end that parses Cypher queries, and a Technology Compatibility Kit (TCK) of over 2000 ...
Gremlin is a graph traversal language and virtual machine developed by Apache TinkerPop of the Apache Software Foundation.Gremlin works for both OLTP-based graph databases as well as OLAP-based graph processors.
The Leiden algorithm is a community detection algorithm developed by Traag et al [1] at Leiden University.It was developed as a modification of the Louvain method.Like the Louvain method, the Leiden algorithm attempts to optimize modularity in extracting communities from networks; however, it addresses key issues present in the Louvain method, namely poorly connected communities and the ...
WASHINGTON – President Donald Trump fired over a dozen inspectors general across federal agencies late Friday night, one of the fired officials confirmed to USA TODAY.
The inspiration for this method of community detection is the optimization of modularity as the algorithm progresses. Modularity is a scale value between −1 (non-modular clustering) and 1 (fully modular clustering) that measures the relative density of edges inside communities with respect to edges outside communities.