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

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

Infinigraph is a new distributed graph architecture that allows Neo4j’s database to run operational and analytical workloads ...

New architecture fuses real-time transactions and analytics in one platform, with breakthrough performance and full fidelity at unprecedented scale Neo4j, the leading graph database and analytics ...

The new distributed graph architecture promises unified transactional and analytical processing, enabling enterprises to ...

When DataStax acquired Aurelius, a graph database startup last year, it was clear it wanted to add graph database functionality to its DataStax Enterprise product, and today it achieved that goal ...

The State of Graph Databases Worldwide A few days ago, IBM released "The State of Graph Databases Worldwide," a report on the adoption and use case characteristics of graph databases.

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 ...

Graph databases facilitate discovery and analysis closely connected facts. This post is one of a series that introduces the fundamentals of NOSQL databases, and their role in Big Data Analytics.

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.