Click to take a quick look at our demos!

Image search	Chatbots	Chemical structure search

Milvus is an open-source vector database built to power AI applications and embedding similarity search. Milvus makes unstructured data search more accessible, and provides a consistent user experience regardless of the deployment environment. Milvus was released under the open-source Apache License 2.0 in October 2019. It is currently an incubation-stage project under [LF AI & Data Foundation](https://lfaidata.foundation/). - **Blazing Fast** Average latency measured in milliseconds on ten million vector datasets. Supports CPU SIMD, GPU, and FPGA accelerations, fully utilizing available hardware resources to achieve cost efficiency. - **Easy to Use** Rich APIs designed for data science workflows. Consistent cross-platform UX from laptop, to local cluster, to cloud. Embed real-time search and analytics into virtually any application. - **Stable and Resilient** Milvus’ built-in replication and failover/failback features ensure data and applications can maintain business continuity in the event of a disruption. - **High Elasticity** Component-level scalability makes it possible to only scale where necessary. - **Community Backed** With over 1,000 enterprise users, 5,000+ stars on GitHub, and an active open-source community, you’re not alone when you use Milvus. > **IMPORTANT** The master branch is for the development of Milvus v2.0. On March 9th, 2021, we released Milvus v1.0, the first stable version of Milvus with long-term support. To use Milvus v1.0, switch to [branch 1.0](https://github.com/milvus-io/milvus/tree/1.0). ## Getting Started ### Demos - [Image Search](https://zilliz.com/milvus-demos): Images made searchable. Instantaneously return the most similar images from a massive database. - [Chatbots](https://zilliz.com/milvus-demos): Interactive digital customer service that saves users time and businesses money. - [Chemical Structure Search](https://zilliz.com/milvus-demos): Blazing fast similarity search, substructure search, or superstructure search for a specified molecule. ## Contributing Contributions to Milvus are welcome from everyone. See [Guidelines for Contributing](https://github.com/milvus-io/milvus/blob/master/CONTRIBUTING.md) for details on submitting patches and the contribution workflow. See our [community repository](https://github.com/milvus-io/community) to learn about our governance and access more community resources. ## Documentation ### Milvus Docs For documentation about Milvus, see [Milvus Docs](https://milvus.io/docs/overview.md). ### SDK The implemented SDK and its API documentatation are listed below: - [Python](https://github.com/milvus-io/pymilvus/tree/1.x) ### Recommended Articles - [What is an embedding vector? Why and how does it contribute to the development of Machine Learning?](https://milvus.io/docs/v1.0.0/vector.md) - [Which vector indexes does Milvus support? Which should I choose?](https://milvus.io/docs/v1.0.0/index.md) - [How does Milvus compare the distance between vectors?](https://milvus.io/docs/v1.0.0/metric.md) - You can learn more in [Milvus Server Configurations](https://milvus.io/docs/v1.0.0/milvus_config.md). ## Contact Join the Milvus community on [Slack Channel](https://join.slack.com/t/milvusio/shared_invite/zt-e0u4qu3k-bI2GDNys3ZqX1YCJ9OM~GQ) to share your suggestions, advice, and questions with our engineering team. You can also submit questions to our [FAQ page](https://milvus.io/docs/v1.0.0/performance_faq.md). Subscribe to our mailing lists: - [Milvus Technical Steering Committee](https://lists.lfai.foundation/g/milvus-tsc) - [Milvus Technical Discussions](https://lists.lfai.foundation/g/milvus-technical-discuss) - [Milvus Announcement](https://lists.lfai.foundation/g/milvus-announce) Follow us on social media: - [Milvus Medium](https://medium.com/@milvusio) - [Milvus CSDN](https://zilliz.blog.csdn.net/) - [Milvus Twitter](https://twitter.com/milvusio) - [Milvus Facebook](https://www.facebook.com/io.milvus.5) ## License Milvus is licensed under the Apache License, Version 2.0. View a copy of the [License file](https://github.com/milvus-io/milvus/blob/master/LICENSE). ## Acknowledgments Milvus adopts dependencies from the following: - Thank [FAISS](https://github.com/facebookresearch/faiss) for the excellent search library. - Thank [etcd](https://github.com/coreos/etcd) for providing some great open-source tools. - Thank [Pulsar](https://github.com/apache/pulsar) for its great distributed information pub/sub platform. - Thank [RocksDB](https://github.com/facebook/rocksdb) for the powerful storage engines.