The intersection of graph and vector databases. With the rise of gen AI, there has been a corresponding growth in the need and demand for vector-capable databases. With a vector, ...

The vector database cloud service may attract developers with performance and cost advantages over traditional databases for AI-related workloads, analysts say. San Francisco-based Zilliz has ...

But now vector databases are finding themselves smack dab in the middle of the hottest workload in tech: large language models (LLMs) such as OpenAI’s GPT-4, Facebook’s LLaMA, and Google’s LaMDA. In ...

Enter vector databases, a new solution designed to handle unstructured data in a way that feels intuitive and context-aware. By representing data as mathematical embeddings—essentially capturing ...

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 ...

As the saying goes, context is everything – and this is certainly the case with AI. To be useful, AI systems need to be able to understand nuance and deliver accurate, relevant results. Our ability to ...

TL;DR Key Takeaways : GraphRAG uses knowledge graphs instead of traditional vector databases, allowing deeper insights and relationships within datasets through structured data representation.

It turns out that AWS customers prefer vector capabilities in existing databases rather than a dedicated vector database offering, according to Sivasubramanian. “They told us they want to use them in ...

Oracle Corp.'s flagship database management system is now available as a cloud service. Oracle Database 23ai features vector search and more than 300 additional major features, with many focused on s ...

Available starting today, Neo4j Aura Graph Analytics is said to work with any kind of data source, including Oracle, Microsoft SQL, Databricks, Google BigQuery, Snowflake and Microsoft OneLake.