A graph database increasingly used for knowledge graphs in AI applications.
Neo4j is a native graph database that stores and queries highly connected data using nodes, relationships, and properties. In AI applications, it's particularly valuable for building knowledge graphs that enhance LLM capabilities through GraphRAG approaches.
For AI applications, Neo4j enables: knowledge graph construction from documents, graph-based retrieval that follows relationships, combining graph queries with vector search, entity resolution and linking, and storing complex domain knowledge that benefits from relationship modeling.
GraphRAG (Graph-based RAG) has emerged as a powerful pattern, using knowledge graphs alongside or instead of pure vector retrieval. Neo4j's vector index capabilities allow hybrid approaches. Engineers should consider Neo4j when: data has rich relationships, multi-hop reasoning is valuable, or domain knowledge is naturally graph-structured. The learning curve for Cypher query language is a consideration.
A graph database increasingly used for knowledge graphs in AI applications.
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