{"data":{"slug":"zilliztech-vectordbbench","name":"VectorDBBench","tagline":"Benchmark for vector databases","github_url":"https://github.com/zilliztech/VectorDBBench","owner":"zilliztech","repo":"VectorDBBench","owner_avatar_url":"https://avatars.githubusercontent.com/u/18416694?v=4","primary_language":"Python","stars":1164,"forks":425,"topics":["benchmark","cost-effectiveness","performance","vector-database","vector-search","vectordb"],"archived":false,"github_pushed_at":"2026-08-14T10:00:47+00:00","maintenance_label":"Active","stars_delta_30d":17,"url":"https://www.graphcanon.com/tools/zilliztech-vectordbbench","markdown_url":"https://www.graphcanon.com/tools/zilliztech-vectordbbench.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/zilliztech-vectordbbench","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=zilliztech-vectordbbench","description":"Benchmark for vector databases.","homepage_url":"https://zilliz.com/vector-database-benchmark-tool","license":"MIT","open_issues":174,"watchers":14,"ai_summary":"A benchmark tool written in Python to assess the performance and cost-effectiveness of various vector databases.","readme_excerpt":"### Install\n**Install vectordb-bench with only PyMilvus**\n```shell\npip install vectordb-bench\n```\n\n**Install the specific database client**\n\n```shell\npip install 'vectordb-bench[pinecone]'\n```\nAll the database client supported\n\n| Optional database client | install command                             |\n|--------------------------|---------------------------------------------|\n| pymilvus, zilliz_cloud (*default*)     | `pip install vectordb-bench`                |\n| qdrant                   | `pip install vectordb-bench[qdrant]`        |\n| pinecone                 | `pip install vectordb-bench[pinecone]`      |\n| weaviate                 | `pip install vectordb-bench[weaviate]`      |\n| elastic, aliyun_elasticsearch| `pip install vectordb-bench[elastic]`       |\n| pgvector, pgvectorscale, pgdiskann, alloydb, vectorchord | `pip install vectordb-bench[pgvector]`      |\n| pgvecto.rs               | `pip install vectordb-bench[pgvecto_rs]`    |\n| redis                    | `pip install vectordb-bench[redis]`         |\n| memorydb                 | `pip install vectordb-bench[memorydb]`      |\n| chromadb                 | `pip install vectordb-bench[chromadb]`      |\n| cockroachdb              | `pip install vectordb-bench[cockroachdb]`   |\n| awsopensearch            | `pip install vectordb-bench[opensearch]` |\n| aliyun_opensearch        | `pip install vectordb-bench[aliyun_opensearch]` |\n| mongodb                  | `pip install vectordb-bench[mongodb]`       |\n| tidb                     | `pip install vectordb-bench[tidb]`          |\n| vespa                    | `pip install vectordb-bench[vespa]`         |\n| oceanbase                | `pip install vectordb-bench[oceanbase]`     |\n| hologres                 | `pip install vectordb-bench[hologres]`      |\n| tencent_es               | `pip install vectordb-bench[tencent_es]`    |\n| alisql                   | `pip install vectordb-bench[alisql]`      |\n| polardb                  | `pip install vectordb-bench[polardb]`       |\n| doris                    | `pip install vectordb-bench[doris]`         |\n| zvec                     | `pip install vectordb-bench[zvec]`          |\n| endee                    | `pip install vectordb-bench[endee]`         |\n| lindorm                  | `pip install vectordb-bench[lindorm]`       |\n| volc_mysql               | `pip install vectordb-bench[volc_mysql]`    |\n| adbpg                    | `pip install vectordb-bench[adbpg]`         |\n\n---\n\n### Install requirements\n``` shell\npip install -e '.[test]'\n\npip install -e '.[pinecone]'\n```\n\n---\n\n### Installation\nThe system under test can be installed in any form to achieve optimal performance. This includes but is not limited to binary deployment, Docker, and cloud services.","github_created_at":"2023-05-10T02:16:41+00:00","created_at":"2026-07-07T17:44:42.261336+00:00","updated_at":"2026-08-21T18:01:56.374278+00:00","categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"}],"tags":[{"slug":"benchmark","name":"benchmark"},{"slug":"cost-effectiveness","name":"cost-effectiveness"},{"slug":"performance","name":"performance"},{"slug":"vector-database","name":"vector-database"},{"slug":"vector-search","name":"vector-search"},{"slug":"vectordb","name":"vectordb"}],"trust":{"provenance":{"is_fork":false,"github_id":638739649,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-21T18:01:55.359Z","maintenance":{"label":"Active","score":82,"methodology":"github_public_v1","releases_90d":0,"days_since_push":7,"last_release_at":"2026-05-15T10:06:45Z","stars_delta_30d":17,"open_issues_delta_30d":20},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:26:28.113Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-21T18:01:55.827Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-08-21T18:01:55.827Z","managed_saas":false},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-08-21T18:01:55.827Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-21T18:01:55.827Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-08-21T18:01:55.827Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-21T18:01:55.827Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When you need a comprehensive performance analysis of vector database solutions using Python","For assessing cost-effectiveness of various vector databases"],"when_not_to_use":["If your evaluation framework requires languages other than Python or licenses other than MIT","When benchmarking non-vector type databases, as VectorDBBench is specialized for vector databases"],"source":"enrich:decision_facts","observed_at":"2026-07-14T19:10:52.419Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"VectorDBBench is a benchmark tool for evaluating vector databases written in Python under the MIT license."}]}}