FAISS
Ranked 6 of 10 vector databases by recommenders
Free library for fast similarity search over vector collections, used for prototyping and local retrieval. Critics say it lacks metadata, update and operational tooling and is not suited to production.
Free library for fast similarity search over vector collections, used for prototyping and local retrieval. Critics say it lacks metadata, update and operational tooling and is not suited to production.
12 people gave an opinion
- recommend it
- 9
- criticize it
- 3
- approval share
- 75%
Recommended in 5 of 13 months
- November 2025: recommended
- December 2025: recommended
- January 2026: recommended
- February 2026: not recommended
- March 2026: recommended
- April 2026: not recommended
- May 2026: not recommended
- June 2026: recommended
- July 2026: not recommended
- August 2026: not recommended
- September 2026: not recommended
- October 2026: not recommended
- November 2026: not recommended (month in progress)
Why it doesn’t carry the badge
- 9 people recommend itNeeds 10 or more, not met.
- 3 recommenders for every criticNeeds 2 to 1 or better, met.
- Recommended in 5 of 13 monthsNeeds 4 or more, met.
The same three rules apply to every product, and the badge can’t be bought. How the badge works
What people say about it
The reasons people give, with the number of comments that give each one. Open a reason to read what they said.
Why people recommend it
Each mark is one comment
Local vector search in agents
“I have production agents which run vector search via FAISS locally”
Comment from 19 Jan 2026 in “Ask HN: How are you doing RAG locally?” “If your data aren't too large, you can use faiss-cpu and pickle”
Comment from 14 Jan 2026 in “Ask HN: How are you doing RAG locally?”
Other vector databases people recommend
The four most recommended other vector databases, with the same counts for each, so you can compare like for like. The tick on each bar marks the 2 to 1 line the badge needs.
| Product | Recommend | Criticize | Approval | Months | Owned | Badge |
|---|---|---|---|---|---|---|
| Qdrant | 22 | 3 | 88% | 10 | — | Approved |
| Chroma | 17 | 5 | 77% | 7 | — | Approved |
| sqlite-vec | 17 | 3 | 85% | 7 | — | Approved |
| turbopuffer | 13 | 2 | 87% | 8 | — | Approved |
| FAISSThis page | 9 | 3 | 75% | 5 | — | — |
What people said
11 of the 12 comments that mention it, newest first. Each links to the original comment.
“FAISS is no longer close to SoTA”
“I've found FAISS great for certain use cases”
“Had to settle for HNSW over FAISS's IVF-PQ, but at this scale the recall tradeoff is fine.”
“a recommender system that would normally need FAISS + XGBoost + SHAP + Isolation Forests + custom code”
“I have production agents which run vector search via FAISS locally”
“Faiss-gpu was impressively fast on the RTX6000 and faiss-cpu is slower on the M1 Ultra but still fast enough for my purposes”
“If your data aren't too large, you can use faiss-cpu and pickle”
“the rest of them OOMKilled (out of memory error)”
“FAISS has been great for prototyping but I'm definitely hitting the limits around metadata, updates, and operational overhead”
“FAISS is not suitable for production.”
“used literally everywhere (even inside OpenAI)”
Counts come from 1,795,640 Hacker News comments, November 2025 to November 2026. How we count. Report a mistake.