Hitting pgvector limits? LanceDB gives you dedicated vector infrastructure — without competing for Postgres resources, managing extension upgrades, or running migrations.
Dedicated vector infrastructure on object storage. Scale independently from your transactional DB. Up to 100x savings.
Raw data, embeddings, and features together. No sync jobs between Postgres and a separate vector store.
Add embedding columns without ALTER TABLE. No pgvector migrations. No downtime.
Vector, full-text, and SQL queries in one system. No extensions to manage.
| PGVector | LanceDB | |
|---|---|---|
| Cost | Extension sharing resources with transactional workloads. | Dedicated object storage with compute-storage separation. Up to 100x savings. |
| Scale | Postgres extension, inherits relational DB scaling constraints. | 20 PB largest table. 20K+ QPS. Billions of vectors. |
| Search | Vector via extension. Full-text via Postgres tsvector. | Native vector, full-text, and SQL hybrid search in one query. |
| Data model | Extension bolted onto relational DB. | Schema evolution - raw data, embeddings, and features in one table. |
| Operations | Constrained by Postgres query planner and vacuum. | Stateless compute. No vacuuming, no connection pooling. |
| Best for | Small vector workloads alongside existing Postgres. | Dedicated vector infrastructure at scale, schema evolution. |
Granular RBAC, SSO integration, and VPC deployment options.
Data versioning and time-travel capabilities for auditability.
Dedicated technical account management and guaranteed SLAs.
Or try LanceDB OSS — same code, scales to Cloud.