Data is no longer small, simple, static, but big, complex and dynamic. In this sense of urgency, Graph Database is created to hover beyond the limit of the current DMBS’s.

The graph database is created using a graph database management system (DBMS) like Neo4j. The Cypher query generated in step 3 is ingested into the DBMS, which creates the nodes and edges in the ...

A graph database is a type of data model structured to help users better understand relationships between different data points and content. There are multiple graph databases in the market today ...

A new semantic-based graph data model has emerged within the enterprise. This data model has all of the advantages of the relational data model, but goes even further in providing for more ...

ArangoDB: Suitable for startups and SMBs, ArangoDB is a multi-model database that supports graph, document, and key/value data models.

The world's only multi-model graph database combining relational (PostgreSQL) and graph model Enterprise graph database that integrates legacy data environment Raising $10 million for AgensGraph ...

This release includes a major change to the graph data model with the introduction of a new schema construct called "labels." The new construct makes it possible for developers essentially to tell the ...

Google popularized the term "knowledge graph" in this 2012 blog post. Since then, there has been a massive momentum around knowledge graphs, which have become increasingly vital in data intelligence ...

An example of a popular graph database system is Neo4j. Another Choice: The Multi-Model DBMS Yet another choice in the NoSQL market is the multi-model DBMS. A growing number of vendors have delivered ...

Automotive giant Daimler is using Neo4j's graph database technology in its HR department. ZDNet spoke to Jochen Linkohr, the manager of HR IT at Daimler, to find out more. ZDNet: When did you ...