qdrant/vector-db-benchmark
Framework for benchmarking vector search engines
Supports benchmarking across multiple vector databases (Qdrant, Weaviate, Milvus, etc.) with pluggable engine implementations and configurable scenarios covering connection, indexing, data upload, and query phases. Uses a distributed server-client architecture with Docker-based engine deployment and Python clients, allowing parameter tuning via JSON configurations and wildcard-based test selection. Integrates datasets automatically via a central registry and produces standardized performance metrics across different hardware setups for comparative analysis.
353 stars.
Stars
353
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139
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 12, 2026
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