VectorDBBench

Comprehensive guide to benchmarking vector databases covering performance testing methodologies, standard benchmarks like ANN-Benchmarks, and best practices for evaluating throughput, latency, and accuracy.

Public benchmark leaderboard comparing vector database performance across multiple cloud and open-source solutions with standardized testing scenarios for production workloads.

Open-source vector database benchmarking tool testing databases across production-critical scenarios including static collection, filtering, and streaming cases with modern embedding model datasets.

PostgreSQL extension that builds on pgvector for higher-performance embedding search with DiskANN indexing. Achieves 28x lower latency and 16x higher throughput than Pinecone at 75% less cost on 50M embeddings.

Automatic RAG Evaluation System - a framework for assessing RAG system quality through automated evaluation of retrieval relevance and generation accuracy without human labels.

Open-source library for preprocessing unstructured documents (PDFs, Word, HTML, images) for RAG and LLM applications. Handles extraction, chunking, and cleaning of diverse document types.