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From FAISS Move vectors from a FAISS index file into Qdrant to gain managed storage, payload filtering, and distributed search. Migrate from FAISS to Qdrant by importing non-quantized FAISS index files into Qdrant collections for managed storage, payload filters, and distributed search. 90

Migrate from FAISS to Qdrant

What You Need from FAISS

  • Index file path — path to your FAISS index file
  • Distance metric — the metric used when the index was built (l2, inner product, etc.)

Supported Index Types

FAISS Index Type Supported Notes
IndexFlatL2 Yes Maps to euclid distance
IndexFlatIP Yes Maps to dot distance
IndexHNSWFlat Yes Full vectors are stored
IndexIVFFlat Yes Full vectors are stored
IndexIVFPQ No Quantized — original vectors not stored
IndexPQ No Quantized — original vectors not stored

Concept Mapping

FAISS Qdrant Notes
Index Collection One-to-one mapping
Vector (by position) Point Position in index becomes point ID

Run the Migration

docker run --net=host --rm -it \
    -v /path/to/your/index:/data \
    registry.cloud.qdrant.io/library/qdrant-migration faiss \
    --faiss.index-path '/data/your-index.index' \
    --qdrant.url 'https://your-instance.cloud.qdrant.io:6334' \
    --qdrant.api-key 'your-qdrant-api-key' \
    --qdrant.collection 'your-collection' \
    --qdrant.distance-metric cosine

All FAISS-Specific Flags

Flag Required Description
--faiss.index-path Yes Path to the FAISS index file (inside the container)

Qdrant-Side Options

Flag Default Description
--qdrant.distance-metric cosine Distance metric: cosine, dot, euclid, or manhattan

Gotchas

  • No metadata: FAISS indexes store only vectors. All points will have empty payloads. If you have a separate metadata store keyed by vector position, import that separately after migration.
  • Point IDs: Points are assigned IDs based on their position in the FAISS index. Use this to join with any external metadata store.

Next Steps

After migration, verify your data arrived correctly with the Migration Verification Guide.