Whether IT leaders opt for the precision of a Knowledge Graph or the efficiency of a Vector DB, the goal remains clear—to harness the power of RAG systems and drive innovation, productivity, and ...

He explained that the new service helps customers analyze existing Neptune graph data or data lakes on top of S3 storage, taking advantage of vector search to find key insights.

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 ...

While graph data is great at representing and analyzing complex relationships and connections, vector data is optimized for efficient search capabilities and calculations in high-dimensional spaces.

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

A number of fast-growing use cases for graph databases are emerging that are highly compelling for data scientists. ... (GNN) to generate vector space representations for the entities in the graph.

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 ...