vector-db-benchmark and VBench
These are competitors—both provide benchmarking frameworks for evaluating vector search performance, though Qdrant's benchmark is more mature and focused on specialized vector databases while VBench targets vector analytics within relational databases.
About vector-db-benchmark
qdrant/vector-db-benchmark
Framework for benchmarking vector search engines
This framework helps you compare the speed and efficiency of different vector search engines. It takes a vector search engine, a dataset (like embeddings for text or images), and a defined test scenario as input. It then measures how well and how quickly the engine performs, providing results to help you choose the best one for your specific needs. This is ideal for machine learning engineers, MLOps specialists, or anyone building or deploying applications that rely on fast and accurate vector search.
About VBench
microsoft/VBench
An Approximate Vector-Analytics Benchmark for Relational Databases
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