PG Vector vs Pinecone
Compare deployment options, cost efficiency, and features to choose the right vector database for your application.
Database Comparison
PG Vector takes the lead.
Both PG Vector and Pinecone are powerful vector databases designed for efficient similarity search and storage. However, their deployment options and features differ in important ways.
Why PG Vector:
- PG Vector ranks higher overall
- PG Vector offers more deployment options
- PG Vector is more cost-effective
- PG Vector has more permissive licensing
- PG Vector has 2 more strengths
PG Vector
PG Vector is a popular Postgres extension that adds vector search capabilities directly inside a traditional relational database. It is ideal for teams that want to keep embeddings, metadata, and application data in one system without operating a separate vector database.
Pinecone
Pinecone is a fully managed, proprietary cloud vector database designed for high-performance RAG pipelines. It abstracts away infrastructure, scaling, replication, and index management. Pinecone is popular among companies building production RAG systems that need predictable latency and fully hosted operations.
Feature Comparison
Infrastructure & Technical Details
| Feature | PG Vector | Pinecone |
|---|---|---|
| Deployment | Self-Hosted, Managed Cloud | Managed Cloud |
| Cost | Free (extension), infra cost only | Storage: $0.33/GB/mo; Write Units: $4/million; Read Units: $16/million; Minimum $50/mo |
| License | PostgreSQL | Proprietary |
| Index Types | Flat, IVFFlat, HNSW | Dense (HNSW-like), Sparse |
| Cloud Providers | AWS RDS, Azure Postgres, GCP AlloyDB, Supabase, Timescale | AWS, Azure, GCP |
| Regional Flexibility | high | low |
| Strengths Count | 9 | 7 |
| Weaknesses Count | 7 | 7 |