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

One technology experiencing a kind of renaissance is the graph database, which has existed for years but is finding new relevance in current cybersecurity contexts.

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.

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 ...

Why graph databases are becoming mainstream and their connection to AI, ML and big data use cases.

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.

As graph database adoption accelerates, new data infrastructures will emerge to eliminate many of the scale struggles of graph database models.

The rise of graph databases is closely related to AI's demand for data processing. AI technology requires vast amounts of structured and unstructured data, which must not only be input into ...

Neo4j, the company behind the open source graph database, has launched a completely free version of its fully-managed cloud service.

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 database startup TigerGraph Inc. today announced a major update to its flagship cloud platform with the Savanna release, bringing with it six times faster network deployments and dozens of ...