Setup Configuration
Vector Stores
Configure vector databases for embedding storage and semantic search in Cognee
Vector stores hold embeddings for semantic similarity search. They enable Cognee to find conceptually related content based on meaning rather than exact text matches.
New to configuration?See the Setup Configuration Overview for the complete workflow:install extras → create
.env → choose providers → handle pruning.Supported Providers
Cognee supports multiple vector store options:- LanceDB — File-based vector store, works out of the box (default)
- PGVector — Postgres-backed vector storage with pgvector extension
- ChromaDB — HTTP server-based vector database
- FalkorDB — Hybrid graph + vector database
- Neptune Analytics — Amazon Neptune Analytics hybrid solution
Configuration
Environment Variables
Environment Variables
Set these environment variables in your
.env file:VECTOR_DB_PROVIDER— The vector store provider (lancedb, pgvector, chromadb, falkordb, neptune_analytics)VECTOR_DB_URL— Database URL or connection stringVECTOR_DB_KEY— Authentication key (provider-specific)VECTOR_DB_PORT— Database port (for some providers)
Setup Guides
LanceDB (Default)
LanceDB (Default)
LanceDB is file-based and requires no additional setup. It’s perfect for local development and single-user scenarios.Installation: LanceDB is included by default with Cognee. No additional installation required.Data Location: Vectors are stored in a local directory. Defaults under the Cognee system path if
VECTOR_DB_URL is empty.PGVector
PGVector
PGVector stores vectors inside your Postgres database using the pgvector extension.Installation: Install the Postgres extras:Docker Setup: Use the built-in Postgres with pgvector:Note: If using your own Postgres, ensure
CREATE EXTENSION IF NOT EXISTS vector; is available in the target database.ChromaDB
ChromaDB
ChromaDB requires a running Chroma server and authentication token.Installation: Install ChromaDB extras:Docker Setup: Start the bundled ChromaDB server:
FalkorDB
FalkorDB
FalkorDB can serve as both graph and vector store, providing a hybrid solution.Installation: Install FalkorDB extras:Docker Setup: Start the FalkorDB service:Access: Default ports are 6379 (DB) and 3001 (UI).
Neptune Analytics
Neptune Analytics
Use Amazon Neptune Analytics as a hybrid vector + graph backend.Installation: Install Neptune extras:Note: URL must start with
neptune-graph:// and AWS credentials should be configured via environment variables or AWS SDK.Important Considerations
Dimension Consistency
Dimension Consistency
Ensure
EMBEDDING_DIMENSIONS matches your vector store collection/table schemas:- PGVector column size
- LanceDB Vector size
- ChromaDB collection schema
Provider Comparison
Provider Comparison
| Provider | Setup | Performance | Use Case |
|---|---|---|---|
| LanceDB | Zero setup | Good | Local development |
| PGVector | Postgres required | Excellent | Production with Postgres |
| ChromaDB | Server required | Good | Dedicated vector store |
| FalkorDB | Server required | Good | Hybrid graph + vector |
| Neptune Analytics | AWS required | Excellent | Cloud hybrid solution |
Notes
- Embedding Integration: Vector stores use your embedding engine from the Embeddings section
- Dimension Matching: Keep
EMBEDDING_DIMENSIONSconsistent between embedding provider and vector store - Performance: Local providers (LanceDB) are simpler but cloud providers offer better scalability