Milvus (vector database)
Open-source distributed vector database
From Wikipedia, the free encyclopedia
Milvus is a distributed vector database developed by Zilliz. It is available as both open-source software and a cloud service called Zilliz Cloud.
| Milvus | |
|---|---|
 | |
| Developer | Zilliz |
| Release | October 19, 2019 |
| Stable release | v3.0.0
/ July 29, 2026.:[1] |
| Written in | Go, C++ |
| Operating system | Linux, macOS |
| Platform | x86, ARM |
| Type | Vector database |
| License | Apache License 2.0 |
| Website | milvus |
| Repository | github |
Milvus is an open-source project under the LF AI & Data Foundation[2] and is distributed under the Apache License 2.0.
History
Milvus has been developed by Zilliz since 2017.[3]
Milvus joined Linux Foundation as an incubation project in January 2020 and became a graduate in June 2021.[2] The details about its architecture and possible applications were presented at ACM SIGMOD Conference in 2021.[4]
Milvus 2.0, a major redesign of the whole product with a new architecture,[5] was released in January 2022.
Milvus 3.0, which introduces elements of data lake / data warehouse based data processing, was released in July 2026. [1]
Features
Similarity search
Various similarity search-related features are available in Milvus:[6]
- In-memory, on-disk and GPU indices,
- Single query, batch query and range query search,
- Support of sparse vectors, binary vectors, JSON and arrays,
- FP32, FP16 and BF16 data types,
- Euclidean distance, inner product distance and cosine distance support for floating-point data,
- Hamming distance and jaccard distance for binary data,
- Support of graph indices (including HNSW), Inverted-lists based indices and a brute-force search.
- Support of vector quantization for lossy input data compression, including product quantization (PQ) and scalar quantization (SQ), that trades stored data size for accuracy,
- Re-ranking.
Milvus' similarity search engine relies on modified forks of third-party open-source similarity search libraries, such as Faiss,[7][8] DiskANN[9][10] (including the AiSAQ [11] technology from KIOXIA) and hnswlib.[12]
Milvus includes optimizations for I/O data layout, specific to graph search indices.[13]
Database
As a database, Milvus provides the following features:[6]
- Support for column-oriented databases
- Four supported data consistency levels, including strong consistency and eventual consistency[14]
- Data sharding
- Streaming data ingestion, which allows processing and ingestion of data in real-time as it arrives
- A dynamic schema, which allows insertion of data without a predefined schema
- Independent storage and compute layers
- Support for multi-tenancy scenarios (database-oriented, collection-oriented, partition-oriented)[15]
- Memory-mapped data storage
- Role-based access control
- Multi-vector and hybrid search[16]
Milvus 3.0 introduces the following features:
- Snapshots
- Nullable vector fields
- Evaluation rollbacks
Data lake
Milvus 3.0 introduces the following[17] large scale operations, applicable for vectors:
Deployment options
Milvus can be deployed as an embedded database, standalone server, or distributed cluster. Zilliz Cloud offers a fully managed version.[18]
GPU support
Milvus provides GPU accelerated index building and search using Nvidia CUDA technology[19][20] via the Nvidia cuVS library,[21] including the GPU-based graph indexing algorithm CAGRA.[22]
Integration
Milvus provides official SDK clients for Java, NodeJS, Python and Go.[23] An additional C# SDK client was contributed by Microsoft.[6][24] The database can integrate with DataDog,[25] Prometheus and Grafana for monitoring and alerts, as well as generative AI frameworks Haystack,[26] LangChain,[27] IBM Watsonx,[28] and those provided by OpenAI.[29][30]
Several storage providers have built integrations with Milvus to support AI workloads and large-scale vector search. These integrations aim to optimize performance, simplify inferencing workflows, and enhance data management capabilities:
Milvus is included in the SUSE AI platform product.[39] [40] Red Hat OpenShift AI self-managed product supports deploying Milvus.[41]
