head to head · open source
faiss vs Qdrant
faiss has 41,256 GitHub stars, 4,586 forks, 327 open issues and last shipped yesterday. Qdrant has 35,414 stars, 2,796 forks, 704 open issues and last shipped yesterday. faiss leads on adoption by 16% (41,256 vs 35,414 stars). faiss is written in C++ under MIT; Qdrant is written in Rust under Apache-2.0. faiss has attracted 11% as many forks as stars, Qdrant 8%. faiss was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| faiss | Qdrant | |
|---|---|---|
| GitHub stars | ★ 41K | ★ 35K |
| License | MIT | Apache-2.0 |
| Written in | C++ | Rust |
| Last push | 2026-11-03 | 2026-11-03 |
| Forks | ⑂ 4.6K | ⑂ 2.8K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick faiss if
- You weight community size — 41K stars and counting
- You want the MIT license terms
- Your stack matches C++
- You value the larger contributor base for long-term maintenance
pick Qdrant if
- You want the Qdrant feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Rust
- You evaluated both and Qdrant fits your workflow better
About faiss
Faiss Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed primarily at Meta's Fundamental AI Research group. News See CHANGELOG.md for detailed information about latest features. Introduction Faiss contains several methods for similarity search. It assumes that…
read the full faiss overview →
About Qdrant
Vector Search Engine for the next generation of AI applications Qdrant (read: quadrant ) is a vector similarity search engine and vector database. It provides a production ready service with a convenient API to store, search, and manage points—vectors with an additional payload. Qdrant is tailored for extended filtering support, making it useful for all sorts of neural network or semantic based matching, faceted search, and other applications. Qdrant is written in Rust 🦀, which makes it fast and reliable even under high load. See benchmarks. With Qdrant, embeddings or neural network encoders can be turned into…
read the full Qdrant overview →
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Frequently asked questions
Is faiss or Qdrant more popular?
faiss has 41,256 GitHub stars and Qdrant has 35,414. faiss has the larger community by that measure.
Are faiss and Qdrant free?
Both are open source. faiss is licensed under MIT and Qdrant under Apache-2.0. Neither carries a licence fee.
What is the difference between faiss and Qdrant?
faiss is written in C++ and Qdrant in Rust. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, faiss or Qdrant?
Choose faiss if you want the larger community (41,256 stars) or its MIT licence terms. Choose Qdrant if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.