You can think of a graph database as a set of interconnected circles (nodes) and each node represents a person, a product, a place or ‘thing’ that we want to build into our data universe.

Data-hungry AI applications are fed complex information, and that's where graph databases and knowledge graphs play a crucial role.

Graph databases are powerful new tools for managing and analyzing heterogeneous data across the enterprise. Most importantly, organizations are beginning tounderstand the specific use cases that graph ...

Still using an RDBMS for friend-of-a-friend queries? Big mistake. Enlist a graph database using Neo4j instead.

Real-time database vendor Aerospike is expanding its multi-model capabilities with the launch of the Aerospike Graph database. Aerospike got its start back in 2009, providing a NoSQL database that ...

Graph databases explicitly express the connections between nodes, and are more efficient at the analysis of networks (computer, human, geographic, or otherwise) than relational databases. There ...

What does graph database actually mean? Find out inside PCMag's comprehensive tech and computer-related encyclopedia.

Newsela uses Dgraph, a “graph database,” to speed the delivery of content while making it easier for the company’s developers to create new features.

Imagine a graph database that's not aimed at the growing graph database market, selling to Fortune 500 without sales, and claiming to be the fastest without benchmarks. Dgraph is unique in some ...

Emerging graph database benchmarks are already helping to overcome performance, scalability and reliability issues.

The flexibility offered by a knowledge-graph-powered data catalog enables near-immediate support for new types of data sources; a knowledge graph makes it easy to extend the model to represent ...