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Milvus Joins LF AI as New Incubation Project

By April 2, 2020No Comments

Milvus, an open source vector similarity search engine, was accepted by the LF AI Foundation (LF AI) as its latest incubation project after TAC voting. LF AI is the organization building an ecosystem to sustain open source innovation in artificial intelligence (AI), machine learning (ML), and deep learning (DL). 

Adopted by over 100 organizations and institutions worldwide, Milvus empowers applications in a variety of fields, including image processing, computer vision, natural language processing, voice recognition, recommender systems, drug discovery, etc. Milvus was originally developed by Zilliz, a Shanghai-based startup company, and open sourced in October 2019.

Zilliz, with the vision of “Reinvent data science”, develops open source data science software for the era of AI and 5G/IoT. “We are pushing forward a globalization strategy that fully incorporates global open source communities. We believe open development leads to greater implementation and greater good for all.” said Starlord, the founder & CEO of Zilliz. “We believe Milvus will help to accelerate the AI adoption for more organizations after joining LF AI.”

“We are very pleased to welcome Milvus to LF AI. Vector similarity search engine is an important component for processing rapidly growing unstructured data. Many AI domains, such as image processing, computer vision, NLP, recommendation systems, and more, could benefit from the capability of Milvus vector similarity search engine. Milvus can help to build up AI applications with open source AI technology,” said Dr. Ibrahim Haddad, Executive Director of LF AI. “We look forward to supporting this project and helping it to thrive under a neutral, vendor-free, and open governance.” 

Milvus is easy-to-use, highly reliable, scalable, robust, and blazing fast, along with a rich list of features. 

  • Comprehensive Similarity Metrics – Milvus offers frequently used similarity metrics, including Euclidean distance, inner product, Hamming distance, Jaccard distance, etc., allowing you to explore vector similarity in the most effective and efficient way possible.
  • Leading-Edge Performance – Milvus is built on top of multiple optimized Approximate Nearest Neighbor Search (ANNS) indexing libraries, including faiss, annoy, hnswlib, etc., thus ensuring that you always get the best performance across various scenarios.   
  • Cost-Efficient – Milvus harnesses the parallelism of modern processors and enables billion-scale similarity searches in milliseconds on a single off-the-shelf server. 
  • Highly Scalable and Robust – You can deploy Milvus in a distributed environment. To increase the capacity and reliability of a Milvus cluster, you can simply add more nodes.
  • Cloud Native – Milvus is designed to run on public cloud, private cloud, or hybrid cloud.

Learn more about Milvus here and be sure to join the Milvus-Announce and Milvus-Technical-Discuss mail lists to join the community and stay connected on the latest updates. 

A warm welcome to Milvus and we look forward to the project’s continued growth and success as part of the LF AI Foundation. LF AI supports projects via a wide range of benefits; and the first step is joining as an Incubation Project. Full details on why you should host your open source project with LF AI are available here.

Milvus Key Links

LF AI Resources


  • Andrew Bringaze

    Andrew Bringaze is the senior developer for The Linux Foundation. With over 10 years of experience his focus is on open source code, WordPress, React, and site security.