feihu618/milvus

An open source embedding vector similarity search engine powered by Faiss, NMSLIB and Annoy

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.

• 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.

Getting Started

Demos

• Image Search: Images made searchable. Instantaneously return the most similar images from a massive database.
• Chatbots: Interactive digital customer service that saves users time and businesses money.
• Chemical Structure Search: 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 for details on submitting patches and the contribution workflow. See our community repository to learn about our governance and access more community resources.

Documentation

Milvus Docs

For documentation about Milvus, see Milvus Docs.

SDK

The implemented SDK and its API documentatation are listed below:

• Python

Recommended Articles

• What is an embedding vector? Why and how does it contribute to the development of Machine Learning?
• Which vector indexes does Milvus support? Which should I choose?
• How does Milvus compare the distance between vectors?
• You can learn more in Milvus Server Configurations.

Contact

Join the Milvus community on Slack Channel to share your suggestions, advice, and questions with our engineering team. You can also submit questions to our FAQ page.

Subscribe to our mailing lists:

• Milvus Technical Steering Committee
• Milvus Technical Discussions
• Milvus Announcement

Follow us on social media:

• Milvus Medium
• Milvus CSDN
• Milvus Twitter
• Milvus Facebook

License

Milvus is licensed under the Apache License, Version 2.0. View a copy of the License file.

Acknowledgments

Milvus adopts dependencies from the following:

• Thank FAISS for the excellent search library.
• Thank etcd for providing some great open-source tools.
• Thank Pulsar for its great distributed information pub/sub platform.
• Thank RocksDB for the powerful storage engines.