LanceDB vs PG Vector
Compare deployment options, cost efficiency, and features to choose the right vector database for your application.
Database Comparison
LanceDB takes the lead.
Both LanceDB and PG Vector are powerful vector databases designed for efficient similarity search and storage. However, their deployment options and features differ in important ways.
Why LanceDB:
- LanceDB ranks higher overall
- LanceDB offers more deployment options
- LanceDB has 4 more strengths
LanceDB
LanceDB is an open-source, AI-native multimodal lakehouse designed for billion-scale vector search. Built on the Lance columnar format, it combines embedded simplicity with cloud-scale performance. LanceDB's disk-based architecture with compute-storage separation enables up to 100x cost savings compared to memory-based solutions while supporting multimodal data (text, images, video, audio).
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.
Feature Comparison
Infrastructure & Technical Details
| Feature | LanceDB | PG Vector |
|---|---|---|
| Deployment | Embedded/Local, Self-Hosted, Managed Cloud (LanceDB Cloud) | Self-Hosted, Managed Cloud |
| Cost | OSS: Free; Cloud: usage-based with $100 free credits; Enterprise: custom pricing | Free (extension), infra cost only |
| License | Apache 2.0 | PostgreSQL |
| Index Types | IVF-PQ, IVF-HNSW-PQ, BTree | Flat, IVFFlat, HNSW |
| Cloud Providers | AWS, Azure, GCP, Any (self-hosted) | AWS RDS, Azure Postgres, GCP AlloyDB, Supabase, Timescale |
| Regional Flexibility | high | high |
| Strengths | 13 | 9 |
| Weaknesses | 9 | 7 |