Qdrant is an Open-Source Vector Database and Vector Search Engine written in Rust. It provides fast and scalable vector similarity search service with convenient API.| qdrant.tech
Use Qdrant's Binary Quantization to enhance the performance and efficiency of OpenAI embeddings| qdrant.tech
pgvector 0.6.0 brings a significant improvement: parallel index builds for HNSW. Building an HNSW index is now up to 30x faster for unlogged tables.| Supabase
The first comparative benchmark and benchmarking framework for vector search engines and vector databases.| qdrant.tech
Binary Quantization is a newly introduced mechanism of reducing the memory footprint and increasing performance| qdrant.tech
Increase performance in pgvector using HNSW indexes| Supabase
We benchmarked several vector databases using various configurations of them on different datasets to check how the results may vary. Those datasets may have different vector dimensionality but also vary in terms of the distance function being used. We also tried to capture the difference we can expect while using some different configuration parameters, for both the engine itself and the search operation separately. Updated: January 2024| qdrant.tech