pgvector vs Pinecone
pgvector lets you add vector search to your existing PostgreSQL — no new infra, familiar SQL, ACID transactions. Pinecone is purpose-built for vectors with better performance at scale. Use pgvector if you already run Postgres and have moderate scale; Pinecone for dedicated vector workloads.
pgvector
Vector search for PostgreSQL
CPostgreSQL Licenseopen-source
Key Features
- PostgreSQL extension
- IVFFlat & HNSW indexes
- Exact & approximate search
- SQL-native queries
- ACID transactions
- Works with any Postgres host
Pricing
Open SourceFree
Use Cases
Adding vectors to existing appsHybrid relational + vectorPrototypingSmall-to-medium datasets
Pinecone
Serverless vector database for AI at scale
Managed ServiceProprietarycloud
Key Features
- Serverless architecture
- Hybrid sparse-dense search
- Metadata filtering
- Namespaces & multi-tenancy
- Real-time index updates
- SOC 2 Type II compliant
Pricing
Free$0
Standard~$0.45/GB/mo
EnterpriseCustom
Use Cases
Semantic searchRecommendation enginesRAG pipelinesAnomaly detection
Verdict
pgvector to stay in Postgres. Pinecone for dedicated, large-scale vector search.
Choose pgvector if you need:
- ✓Complete control over deployment and data
- ✓Source code access for customization
- ✓PostgreSQL extension
- ✓IVFFlat & HNSW indexes
- ✓Exact & approximate search
Choose Pinecone if you need:
- ✓Serverless scaling and managed operations
- ✓Serverless architecture
- ✓Hybrid sparse-dense search
- ✓Metadata filtering