VectorDBBench(VDBBench): A Benchmark Tool for VectorDB

What is VDBBench

VDBBench is not just an offering of benchmark results for mainstream vector databases and cloud services, it's your go-to tool for the ultimate performance and cost-effectiveness comparison. Designed with ease-of-use in mind, VDBBench is devised to help users, even non-professionals, reproduce results or test new systems, making the hunt for the optimal choice amongst a plethora of cloud services and open-source vector databases a breeze.

Understanding the importance of user experience, we provide an intuitive visual interface. This not only empowers users to initiate benchmarks at ease, but also to view comparative result reports, thereby reproducing benchmark results effortlessly. To add more relevance and practicality, we provide cost-effectiveness reports particularly for cloud services. This allows for a more realistic and applicable benchmarking process.

Closely mimicking real-world production environments, we've set up diverse testing scenarios including insertion, searching, and filtered searching. To provide you with credible and reliable data, we've included public datasets from actual production scenarios, such as SIFT, GIST, Cohere, and a dataset generated by OpenAI from an opensource raw dataset. It's fascinating to discover how a relatively unknown open-source database might excel in certain circumstances!

Prepare to delve into the world of VDBBench, and let it guide you in uncovering your perfect vector database match.

VDBBench is sponsored by Zilliz，the leading opensource vectorDB company behind Milvus. Choose smarter with VDBBench - start your free test on zilliz cloud today!

Leaderboard: https://zilliz.com/benchmark

🎈 Announcement 🎈

June 2026 update: Full Text Search has landed in VectorDBBench. We now benchmark BM25-style retrieval across supported backends, starting with MS MARCO and HotpotQA datasets, payload profiles, recall, QPS, and load metrics ready to compare. See the VectorDBBench Full Text Search Release Note for the full rollout details and caveats.

Quick Start

Prerequirement

python >= 3.11

Install

Install vectordb-bench with only PyMilvus

pip install vectordb-bench

Install the specific database client

pip install 'vectordb-bench[pinecone]'

All the database client supported

Optional database client	install command
pymilvus, zilliz_cloud (default)	pip install vectordb-bench
qdrant	pip install vectordb-bench[qdrant]
pinecone	pip install vectordb-bench[pinecone]
weaviate	pip install vectordb-bench[weaviate]
elastic, aliyun_elasticsearch	pip install vectordb-bench[elastic]
pgvector, pgvectorscale, pgdiskann, alloydb, vectorchord	pip install vectordb-bench[pgvector]
pgvecto.rs	pip install vectordb-bench[pgvecto_rs]
redis	pip install vectordb-bench[redis]
memorydb	pip install vectordb-bench[memorydb]
chromadb	pip install vectordb-bench[chromadb]
cockroachdb	pip install vectordb-bench[cockroachdb]
awsopensearch	pip install vectordb-bench[opensearch]
aliyun_opensearch	pip install vectordb-bench[aliyun_opensearch]
mongodb	pip install vectordb-bench[mongodb]
tidb	pip install vectordb-bench[tidb]
vespa