These include updates to its Spanner SQL database, which now features graph and vector search support, as well as extended full-text search capabilities.

Graph databases are making a splash in the database market, with specialist, multimodal and cloud database suppliers jostling for a slice of the pie.

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

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

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

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

Neo4j, the graph database and analytics leader, is announcing a partnership with Snowflake that brings Neo4j's fully integrated, native graph data science solution to the Snowflake AI Data Cloud. This ...

The addition of vectors provides context to the graph database for enhanced search and supports generative AI and large language models.

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.

SQL is immensely popular as a query language for databases. Unfortunately, it doesn’t work for nested queries across heterogenous data the same way GraphQL does.