Graph database vendor Neo4j announced today new capabilities for vector search within its graph database. Neo4j’s namesake database technology enables organizations to create a knowledge graph ...

The intersection of large language models and graph databases is one that’s rich with possibilities. The folks at property graph database maker Neo4j today took a first step in realizing those ...

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.

Knowledge Graphs vs. Vector DBs: Similarities and Differences To help understand both the technology and the business impact, it’s important to understand what each of them do.

Vector databases are designed for efficient storage, retrieval and similarity search of vector data and are a key building block for generative AI systems.

TigerGraph, the enterprise AI infrastructure and graph database leader, is releasing its next generation graph and vector hybrid search, delivering the industry's 'most advanced' solution for ...

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