Qdrant

Open-source vector database and similarity search engine. Specializes in high-performance ANN search for production ML workloads. Competes with Pinecone, Weaviate, Milvus.

Notable Contributions

TurboQuant (Qdrant 1.18) — rotation-based vector quantization; extends Google Research’s TurboQuant paper with anisotropy compensation (per-coordinate calibration), length renormalization from RaBitQ, full L2/dot/cosine support, and SIMD kernels. Results: 8× compression at SQ-level recall; +10–20 pp recall over BQ at 16×/32× storage.

Scalar Quantization — int8 per coordinate, 4× compression, near-lossless.

Binary Quantization — 1-bit/2-bit storage, 16×–32× compression.

People

• Ivan Pleshkov
• Jonas Schulz

Articles

• TurboQuant in Qdrant

• Choosing a Vector Database for ANN Search at Reddit — qualitative score 292 vs Milvus 281; better raw latency but lost on Go ecosystem fit and automatic rebalancing

Tools

• Qdrant Vector DB