Qdrant Updated Benchmarks 2024 - Qdrant

This post introduces updated benchmarks for Qdrant, comparing its performance against other vector search engines. Key changes include applying suggestions for more efficient engine operation, resulting in up to four times improvement in certain cases. A new dataset of 1 million OpenAI embeddings for RAG applications has been added. The benchmark methodology now separates latency and requests-per-second (RPS) scenarios, simulating 1 or 100 parallel readers. The post reiterates Qdrant's commitment to open-source, accessible benchmarks, and focuses on production-ready vector databases over indexing libraries.