Graph databases and knowledge graphs—especially when combined—fulfill this role. This is part of a rapidly unfolding movement in which “databases have evolved from merely storage layers for ...

Graph Retrieval-Augmented Generation (GraphRAG) has emerged as an innovative solution to address the limitations of traditional RAG methods. Unlike its predecessor, GraphRAG retrieves graph elements ...

Modern graph database query languages such as GQL, SQL/PGQ, and Cypher allow regular path queries to return entire paths, as opposed to only their endpoints. This is challenging for query evaluation, ...

There is no universal ‘best’ vector database—the choice depends on your needs. Evaluating scalability, functionality, performance, and compatibility with your use cases is vital.

Neo4j is one such database. It’s open source, uses an SQL-like query language, follows the Property Graph Data Model and supports indexes, UNIQUE constraints and full ACID rules.

Graph databases are finding new use cases in sales, ecommerce, healthcare, financial services, fraud detection and much more.

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

After introducing the first fully managed version of its graph database just over nine months ago, Neo4j Inc. today is doubling down with a free tier that it says any developer can use forever ...