Neo4j also trumpeted the value of graphs as vector databases used in generative artificial intelligence. AI training requires ...

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

New architecture fuses real-time transactions and analytics in one platform, with breakthrough performance and full fidelity at unprecedented scale ...

With the rapid development of artificial intelligence (AI) technology, the graph database market is experiencing unprecedented growth, with an annual growth rate approaching 25%. Graph databases are ...

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.

Imagine your database of choice blown out of the water by a startup emerging from stealth. TigerGraph may have done just that for graph databases.

Graph databases that use nodes and properties to represent and store data appear to be making significant inroads in the U.S. retail market. For example, graph database specialist Neo Technology of ...

DataStax recently announced a new product called DataStax Graph to store graph data models. It's based on open source Titan graph database and uses Apache Tinkerpop framework's Gremlin query ...

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.