ANN-Benchmarks is a benchmarking platform specifically for evaluating the performance of approximate nearest neighbor (ANN) search algorithms, which are foundational to vector database evaluation and comparison.

BEIR (Benchmarking IR) is a benchmark suite for evaluating information retrieval and vector search systems across multiple tasks and datasets. Useful for comparing vector database performance.

A collection of datasets curated by Intel Labs specifically for evaluating and benchmarking vector search algorithms and databases.

VectorDBBench is a benchmarking tool developed by ZillizTech for evaluating the performance of various vector databases, aiding users in selecting suitable vector database solutions for their needs.

HAKES is a system designed for efficient data search using embedding vectors at scale, making it a relevant solution for vector database applications.

Qwak provides a vector store solution engineered for optimized storage and querying of vector embeddings, offering efficient search capabilities, high performance, scalability, and data retrieval by identifying similarities among data points.