Milvus is the world's fastest similarity search engine for massive-scale feature vectors. Built with heterogeneous computing architecture for the best cost efficiency. Searches over billion-scale vectors take only milliseconds with minimum computing resources.
Milvus provides stable [Python](https://pypi.org/project/pymilvus/), [Java](https://milvus-io.github.io/milvus-sdk-java/javadoc/io/milvus/client/package-summary.html) and C++ APIs.
See the [Milvus install guide](https://www.milvus.io/docs/en/userguide/install_milvus/) for using Docker containers. To install Milvus from source code, see [build from source](install.md).
Try running a program with Milvus using [Python](https://www.milvus.io/docs/en/userguide/example_code/) or [Java example code](https://github.com/milvus-io/milvus-sdk-java/tree/master/examples).
Contributions are welcomed and greatly appreciated. Please read our [contribution guidelines](CONTRIBUTING.md) for detailed contribution workflow. This project adheres to the [code of conduct](CODE_OF_CONDUCT.md) of Milvus. By participating, you are expected to uphold this code.
We use [GitHub issues](https://github.com/milvus-io/milvus/issues/new/choose) to track issues and bugs. For general questions and public discussions, please join our community.
To connect with other users and contributors, welcome to join our [Slack channel](https://join.slack.com/t/milvusio/shared_invite/enQtNzY1OTQ0NDI3NjMzLWNmYmM1NmNjOTQ5MGI5NDhhYmRhMGU5M2NhNzhhMDMzY2MzNDdlYjM5ODQ5MmE3ODFlYzU3YjJkNmVlNDQ2ZTk).