With today’s updates to its managed graph database for the cloud, Neo4j AuraDB, the San Mateo, California-based company is working to make it easier for users to get started with its graph database.

Graph databases are beneficial for applications like knowledge graphs, recommendation systems, and semantic search engines because they are excellent at capturing semantic context.

From Relational to Graph Databases: The 'Association' Revolution in the Era of Big Data In this era of information explosion, ...

Aerospike this week rolled out new graph database offering that leverages open source components, including the TinkerPop graph engine and the Gremlin graph query language. The NoSQL company foresees ...

Although databases that focus on the relational aspect of data analytics abound, few are as effective at revealing the hidden valuable insights as a graph database.

Graph databases are beneficial for applications like knowledge graphs, recommendation systems, and semantic search engines because they are excellent at capturing semantic context.

Relational databases are so entrenched and ubiquitous that we reflexively use them for new application requirements. However, graph databases are better for applications with specific processing ...

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

While still a bit of an outlier, graph-oriented databases continue to find a role in the modern data stack -- thanks largely to AI.

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