Neo4j Vector Index
FreemiumVector search on Neo4j graph database — combine embeddings with knowledge graphs.
Tool Info
Overview
Neo4j Vector Index lets you store and query embeddings alongside graph nodes and relationships.
Essential for GraphRAG where entity structure matters as much as semantic similarity.
Pairs with Cypher for hybrid graph-vector retrieval.
Features
- Vector indexes in Cypher
- Graph traversal + vectors
- AuraDB managed
- LangChain integration
Pricing
Pros
- Unique graph + vector combo
- GraphRAG native
- Enterprise graph maturity
Best For
When NOT to Use
- Graph DB learning curve
- Not a pure vector DB
Typical Users
Related Tools
Alternatives
Related Architecture Guides
Tags
Related Guides
- Knowledge Graphs
Structured representations of entities and relationships - the foundation for GraphRAG, enterprise search, and neuro-symbolic AI.
- GraphRAG
Explore how knowledge graphs enhance RAG pipelines with structured relationships and reasoning.
- Vector Databases
Purpose-built databases for storing, indexing, and querying embedding vectors at scale.
- Vector Search
Understand how vector databases find similar items using high-dimensional embedding comparisons.
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