FAISS vs Qdrant
A neutral, data-driven comparison — live metrics, use-case guidance and FAQ to help you pick.
At a glance
| FAISS | Qdrant | |
|---|---|---|
| GitHub stars | 40,308 | 32,389 |
| PyPI downloads / mo | 17,779,635 | 23,963,183 |
| License | MIT | Apache-2.0 |
| Type | library | database |
| Self-hostable | Yes | Yes |
| Managed option | — | Qdrant Cloud |
| Latest release | v1.14.3 | v1.18.2 |
Which should you choose?
💡 Engineer's take: your hands-on notes from real usage go here — the one thing a data table cannot give a reader.
What they are
FAISS: A library for efficient similarity search and clustering of dense vectors.
Qdrant: Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/