vs

pgvector vs pgvectorscale

pgvector: The standard Postgres extension for vector similarity search with HNSW and IVFFlat indexes. pgvectorscale: TigerData's Postgres extension adding StreamingDiskANN indexes on top of pgvector.

key differences

  • pgvectorscale is built for larger datasets (≤ 1 PB) than pgvector (≤ 10 TB).
  • Horizontal scaling is addon in pgvector and none in pgvectorscale.

choose pgvector for

  • +Adding semantic search to an existing Postgres app
  • +RAG with permission filtering via SQL joins
  • +Recommendations next to product data
  • +Deduplication and similarity lookups

best at · Vector search, RAG, OLTP

choose pgvectorscale for

  • +Large pgvector tables that no longer fit HNSW in RAM
  • +Cost-efficient RAG on Postgres
  • +Filtered semantic search with labels

best at · Vector search, RAG, OLTP

overview
Primary model
Vector
Vector
Also supports
Relational
Relational
Type
Extension
Extension
Status
Active
Active
Developer
Andrew Kane and pgvector contributors
TigerData (formerly Timescale)
First release
2021
2024
Latest version
0.8.7 (Oct 1, 2026)
0.9.1 (Sep 4, 2026)
License
Open source (permissive)PostgreSQL License
Open source (permissive)PostgreSQL License
Free tier
✓
✓
popularity
WhichDB Score
40.0
13.9
Rank
#44
#243
GitHub stars
23.5K
3.2K
Stack Overflow questions
91
–
scale & guarantees
Comfortable data size
Medium (≤ 10 TB)
Large (≤ 1 PB)
Horizontal scaling
Addon
None
Multi-region
Read replicas
Read replicas
ACID
Full
Full
Consistency
Strong
Strong
Schema
Strict
Strict
Architecture
Single node, Primary replica, Client server
Single node, Primary replica, Client server
deployment
Self-hosted
✓
✓
Vendor-managed cloud
—
—
Serverless
—
—
Embedded
—
—
Edge
—
—
Clouds
AWS, Google Cloud, Azure, DigitalOcean, Heroku, Render
AWS, Azure
capabilities
Transactions
✓
✓
Joins
✓
✓
Secondary indexes
✓
✓
Full-text search
✓
✓
Vector search
✓
✓
Geospatial
—
—
JSON
✓
✓
Change data capture
✓
✓
Triggers
✓
✓
Stored procedures
✓
✓
Materialized views
✓
✓
TTL / expiry
—
—
Pub/Sub
✓
✓
Columnar storage
—
—
In-memory
—
—
Durable persistence
✓
✓
Compression
✓
✓
Encryption at rest
—
—
Role-based access
✓
✓
Time travel
—
—
Branching
—
—
Online schema changes
✓
✓
Streaming ingest
—
—
Offline sync
—
—
Runs in WebAssembly
—
—
interfaces
Query languages
SQL
SQL
Client languages
Python, JavaScript, Go, Java, Ruby, Rust, C#, PHP
Any PostgreSQL driver
Best for
Vector search, RAG, OLTP
Vector search, RAG, OLTP

pgvector vs pgvectorscale: FAQ

What is the difference between pgvector and pgvectorscale?

pgvector: The standard Postgres extension for vector similarity search with HNSW and IVFFlat indexes. pgvectorscale: TigerData's Postgres extension adding StreamingDiskANN indexes on top of pgvector. pgvectorscale is built for larger datasets (≤ 1 PB) than pgvector (≤ 10 TB). Horizontal scaling is addon in pgvector and none in pgvectorscale.

When should I choose pgvector over pgvectorscale?

Choose pgvector for adding semantic search to an existing Postgres app, RAG with permission filtering via SQL joins and recommendations next to product data. Choose pgvectorscale for large pgvector tables that no longer fit HNSW in RAM, cost-efficient RAG on Postgres and filtered semantic search with labels.

Is pgvector or pgvectorscale more popular?

pgvector ranks #44 on the WhichDB Score (40.0/100) and pgvectorscale ranks #243 (13.9/100). Popularity is not fit: check the requirements that matter for your project.

Are pgvector and pgvectorscale open source?

Yes. pgvector is open source. License: PostgreSQL License. Yes. pgvectorscale is open source. License: PostgreSQL License.