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The previous description was outdated: it claimed that enabling this option "blocks updates at the request level" until segments are re-optimized. In practice the implementation uses "deferred points": new points written to large unoptimized segments are persisted but excluded from read/search results until the segments are optimized. Updates are not blocked; only `wait=true` clients are made to wait for the deferred points to become visible. Update this in the REST schema (via `OptimizersConfig` / `OptimizersConfigDiff`), in the gRPC proto, in the edge config docstrings, and regenerate the OpenAPI bundle via `tools/generate_openapi_models.sh`. Co-authored-by: Cursor Agent <agent@cursor.com> Co-authored-by: Cursor <cursoragent@cursor.com>
Qdrant Edge
Qdrant Edge is a lightweight, in-process vector search engine designed for embedded devices, autonomous systems, and mobile agents. It enables on-device retrieval with minimal memory footprint, no background services, and optional synchronization with Qdrant Cloud.
For connecting to remote Qdrant instances, use the qdrant-client package instead.
- Website: https://qdrant.tech/edge/
- Documentation: https://qdrant.tech/documentation/edge/
- Examples: https://github.com/qdrant/qdrant/tree/dev/lib/edge/python/examples