pgvector vs 
FAISS
pgvector vs FAISS compared for 2026 — features, license, ease of use, performance and which one to choose. Vector search inside PostgreSQL vs The reference library for similarity search.
Updated regularly · curated by OpenSourceAI.tech
pgvector vs FAISS at a glance
| Spec | pgvector | FAISS |
|---|---|---|
| Category | Vector database | Vector database |
| Type | Postgres extension | Vector search library |
| License | PostgreSQL | MIT |
| Runs locally | Self-hosted | Yes |
| Primary language | C | C++/Python |
| Ease of use | Beginner | Advanced |
| Best for | teams already running PostgreSQL | raw performance and research-grade control |
| GitHub stars | — | — |
Feature comparison
| Feature | pgvector | FAISS |
|---|---|---|
| Self-hostable | ✓ | ✓ |
| Managed cloud | ✓ | ✗ |
| Metadata filtering | ✓ | ✗ |
| Hybrid search | ✓ | ✗ |
| Horizontal scaling | ✓ | ✗ |
| REST API | ✗ | ✗ |
How pgvector and FAISS score
| Criterion | pgvector | FAISS |
|---|---|---|
| Popularity | n/a | n/a |
| Maintenance | n/a | n/a |
| Ease of use | 5.0 | 2.5 |
| Privacy | 4.5 | 5.0 |
| License freedom | 5.0 | 5.0 |
Scores are computed automatically from public signals — GitHub stars (popularity), recent commit activity (maintenance), license type (freedom), local-first design (privacy) and onboarding complexity (ease of use). Indicative, not a verdict.
What each one is
pgvector
pgvector is a PostgreSQL extension that adds vector similarity search to your existing database, so you can do RAG without a separate vector store.
- No new infrastructure — it is just Postgres
- Keep vectors next to relational data
- Mature, well-supported ecosystem
FAISS
FAISS from Meta is the foundational C++/Python library for efficient vector similarity search and clustering — billions of vectors, dozens of index types, CPU and GPU.
- Industry-standard algorithms, battle-tested at Meta scale
- Unmatched index variety (IVF, HNSW, PQ...)
- GPU acceleration for massive datasets
Key differences
pgvector is postgres extension, while FAISS is vector search library. Their licenses differ (PostgreSQL vs MIT), which matters if you ship a commercial product. pgvector leans more beginner-friendly, whereas FAISS is more suited to advanced users. They also differ in how they run (Self-hosted vs Yes). In short, pgvector fits teams already running PostgreSQL, and FAISS fits raw performance and research-grade control.
Which should you choose?
Choose pgvector for teams already running PostgreSQL. Choose FAISS for raw performance and research-grade control.
There is rarely one winner — many setups use both. The right pick depends on your hardware, your team's skills, and whether you value simplicity or control.
Frequently asked questions
Is pgvector or FAISS easier to use?
pgvector is generally the easier of the two to get started with, while FAISS rewards more setup with more control.
Are pgvector and FAISS free?
pgvector is free and open source (PostgreSQL), and FAISS is free and open source (MIT). Neither charges for the core software.
Can I run pgvector and FAISS locally?
pgvector: self-hosted · FAISS: yes. Both can be used without sending your data to a third-party cloud where their setup allows.
pgvector vs FAISS — which should I pick in 2026?
Choose pgvector for teams already running PostgreSQL. Choose FAISS for raw performance and research-grade control.
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