LanceDB vs Qdrant API + MCP

LanceDB

Embedded, no server, and tables can live directly in S3, GCS or Azure storage. No self-serve hosted API. Enterprise is sold through a contact form.

Qdrant API + MCP

Database keys can be read-only, limited to chosen collections and expire after 90 days by default. The MCP server has 2 tools, can't manage collections or run filtered queries, and last released on 10 December 2025.

LanceDB

1. Use it through the Python or TypeScript library. There's no public endpoint an agent can call without an Enterprise deployment
2. Build an FTS index before calling query_type="hybrid", or hybrid search has no keyword side
3. Call optimize() after many small writes, since each write adds a new file version
4. Use select() to drop the vector column from results unless the task needs it
5. On object storage, set a read consistency interval if several processes write the same table

Qdrant API + MCP

1. Create payload indexes on the fields you filter on, or filtered search slows on large collections
2. Use /points/query with prefetch to fuse dense and BM25 results
3. Pass wait=true on upserts when the next step reads its own writes
4. On 429, wait for the Retry-After seconds before retrying
5. Set with_vector=false unless the task needs vectors, since they dominate response size