Milvus
ZillizMilvus is a distributed vector database for approximate nearest-neighbor search over billions of vectors. Hybrid search combines vector similarity with scalar filtering and BM25 full-text search, over index types from HNSW to DiskANN. The project belongs to the LF AI & Data Foundation, and Zilliz, its main contributor, runs the managed Zilliz Cloud service.
Openness
5 high confidence- license
- Apache-2.0
- source
- public
- core features withheld
- no
Milvus is published in full under Apache-2.0, and the same repository builds the standalone and distributed deployments people run themselves. Zilliz, its main contributor, sells Zilliz Cloud as a managed service beside it rather than as a tier holding part of the engine back.
- https://en.wikipedia.org/wiki/Milvus_(vector_database) recorded 2026-08-13
Infobox license Apache License 2.0; joined LF AI & Data January 2020 and "became a graduate in June 2021", citing the foundation's graduation announcement.
- https://github.com/milvus-io/milvus recorded 2026-08-13
Repo page - "Apache-2.0 license", 45,627 stargazers, docker-compose standalone install in the README, Zilliz Cloud referenced as the managed service rather than as a tier holding functionality back. No enterprise directory or separately licensed tree.
- https://github.com/milvus-io/milvus/blob/master/LICENSE recorded 2026-08-13
Full Apache License 2.0 text (11,357 bytes), served from raw.githubusercontent for the master branch.
- https://raw.githubusercontent.com/milvus-io/milvus/master/LICENSE recorded 2026-09-28
The master-branch LICENSE file is the full Apache License text, headed "Apache License" and "Version 2.0, January 2004".
- https://raw.githubusercontent.com/milvus-io/milvus/master/README.md recorded 2026-09-28
The README says the project is hosted "under [LF AI & Data Foundation]" and "distributed with [Apache 2.0]", with Zilliz as its major contributor, documents "Standalone mode" and Milvus Lite for self-hosting, and names Zilliz Cloud only as the managed option: "Milvus is available as a fully managed service on Zilliz Cloud". Searched the body for enterprise edition, license key and commercial license: none; the word enterprise appears only where it describes the open build's security features and its users.
Adoption
3 medium confidenceMilvus is a server. Its Python client, pymilvus, is left out because client installs can vary independently of server deployments. The score comes from Docker Hub pulls of the server image averaged over the image's lifetime, so for a product still growing it is a floor rather than a ceiling. Zilliz's own round figure for Docker pulls runs higher than the registry's count and does not say what it adds.
- https://hub.docker.com/v2/repositories/milvusdb/milvus/ recorded 2026-09-24
"pull_count": 79015004 cumulative pulls of milvusdb/milvus, "date_registered": "2019-06-16", about 905,000 a month over the image's lifetime
- https://pypistats.org/api/packages/pymilvus/recent recorded 2026-09-24
"last_month":3601454 downloads of pymilvus, the client package left out of the level
- https://ungh.cc/repos/milvus-io/milvus recorded 2026-09-24
"stars":46245 for milvus-io/milvus. Corroboration only; a star count is not a use.
Capability
4 high confidenceMilvus is a complete, durable, cluster-capable retrieval system that scales horizontally with compute and storage separated, combining dense vector search with BM25 full-text search. It is one step behind Vespa, which also hosts and evaluates ranking or embedding models inside its serving path, something the evidence for Milvus does not show.
- https://github.com/milvus-io/milvus recorded 2026-08-18
Repo page - vector database feature set, standalone and distributed deployment.
- https://milvus.io/docs/architecture_overview.md recorded 2026-09-30
Architecture overview says the database takes a systemic approach to cloud-nativity, "separating compute from storage and allowing you to scale both up".
- https://milvus.io/docs/full-text-search.md recorded 2026-09-30
Full-text search page says "Milvus provides full text search powered by the BM25 relevance algorithm".
- https://raw.githubusercontent.com/milvus-io/milvus/master/README.md recorded 2026-09-30
README says Milvus has a "fully-distributed and K8s-native architecture" that can scale horizontally and handle "billions of vectors", offers index types including "HNSW, IVF, FLAT (brute-force), SCANN, and DiskANN", and supports "full text search" with BM25.
Verified 2026-09-24