FAISS - Efficient Similarity Search

Facebook AI's library for billion-scale vector similarity search.

When to use FAISS

Use FAISS when:

• Need fast similarity search on large vector datasets (millions/billions)
• GPU acceleration required
• Pure vector similarity (no metadata filtering needed)
• High throughput, low latency critical
• Offline/batch processing of embeddings

Metrics:

• 31,700+ GitHub stars
• Meta/Facebook AI Research
• Handles billions of vectors
• C++ with Python bindings