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

A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its ...

Peter Neubauer introduces Graph databases and how they compare to RDBMS' and where they stand in the NOSQL-movement, followed by examples of using a graph database in Java with Neo4j.

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 ...

The flexibility of the graph data model is a key factor driving the recent surge in graph database popularity. The same requirements for availability and massive scale that drove the development ...

Key Benefits of a Graph Database Better, Faster Queries and Analytics: Graph databases offer superior performance for querying related data, big or small. The graph model offers an inherent indexed ...

Graph is a data model that has long lingered on the fringe of mainstream adoption. But that is changing, as graph lends itself well to representing many real world problems, and the technology is ...

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 ...

The new database adds a property graph data model to the existing capabilities of its NoSQL Database and Apache TinkerPop graph compute engine.

The Graph Database Market is expected to reach USD 2,143.0 million by 2030 from USD 507.6 million in 2024, at a Compound Annual Growth Rate (CAGR) of 27.1 % from 2024–2030, according to a new ...