Benchmark results and tools by MyScale aimed at measuring the performance of vector databases in various search and retrieval tasks.

A set of benchmarks provided by Qdrant for evaluating vector databases, focusing on speed, scalability, and accuracy of vector search operations.

Milvus WebUI provides management for the scalable open-source vector DB ecosystem, enabling oversight of HNSW/IVF/NGT indexed collections in distributed/cluster/embedded Milvus modes. Supports monitoring of GPU-accelerated, billion-scale, real-time multi-modal operations. Facilitates RAG, recommendations, image/video search management; pairs with self-hosted Milvus vs Pinecone/Weaviate alternatives.

Open-source comparative benchmarks evaluating vector search performance of engines like Qdrant, Elasticsearch, Milvus, Redis, and Weaviate. Covers single-node upload/search, filtered search across various datasets and configurations, focusing on RPS, latency, precision, and indexing time using affordable hardware.

Research paper introducing LeanVec, a technique to accelerate vector search by reducing vector dimensionality while preserving search accuracy. Published as an arXiv preprint in 2023 by Mariano Tepper et al.

Optimization technique that allows HNSW vector searches to exit early when the candidate queue remains saturated, reducing latency and resource usage with minimal recall impact.