Take a quick look at our demos!

Image search	Chatbots	Chemical structure search

Milvus is an AI-infused database geared towards (embedding) vector similarity search. Milvus is dedicated to lowering the bar for unstructured data search and providing a consistent user experience regardless of users' 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/). - **Functionality-level Autoscaling** With the main functionalities implemented equivalent among nodes, Milvus is able to autoscale at the functionality level, providing the foundation for a more efficient resource scheduling. - **Hybrid Search** In addition to vectors, basic numeric types, such as boolean, integer, floating-point number, etc, are introduced in Milvus. Search for data from hybrid fields are now supported in the Milvus collection. - **Combined Data Storage** Milvus has reinforced its support for both streaming and batch data persistence and for the adaptation of alternative message/storage engines, in response to users' increasing demand for high database throughput. - **Multiple Indexes in a Single Field** Milvus now supports multiple indexes in a single vector filed, and it decouples indexing from querying. Users are allowed to maintain multiple indexes simultaneously and switch flexibly among them according to their needs. > **IMPORTANT** The master branch is for the development of Milvus v2.0. On March 9th, 2021, we released Milvus v1.0 which is our first stable version of Milvus with long-term support. To try out Milvus v1.0, switch to [branch 1.0](https://github.com/milvus-io/milvus/tree/1.0). ## Getting Started ### To install a Milvus stand-alone See [Install Milvus Standalone](). ### To install a Milvus cluster See [Install Milvus Cluster](). ### 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 document 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) - [What types of vector index 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 engineer team. You can also ask for help at our [FAQ page](https://milvus.io/docs/v1.0.0/performance_faq.md). You can subscribe to our mailing lists at: - [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) and 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.