Qdrant ANN-Filtering-Benchmark-Datasets

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.

Billion-scale benchmark dataset containing 128-dimensional SIFT descriptors of one billion images. Widely used standard for evaluating approximate nearest neighbor search algorithms at scale.

ClickHouse is a columnar OLAP database with vector indexes (ANN via AMM, brute-force), supporting SQL queries over vectors + structured data at petabyte scale. Excels in aggregations with vectors. For analytics workloads with embeddings; faster ingestion than Postgres pgvector for big data.

HVS is an open-source, self-hosted graph-based ANN index using Voronoi diagrams for high-dimensional vector similarity search. Key features include hierarchical graphs, efficient large-scale queries, and free use. Suited for RAG embedding storage/search prototypes, cost-free self-hosting vs Pinecone.

NGT (Neighborhood Graph and Tree) is an open-source vector search engine designed for fast and scalable approximate nearest neighbor search.

KGraph is an open-source library for fast approximate nearest neighbor search in high-dimensional vector spaces, applicable to vector database solutions.