© 2026 AI-Buzz. Early access — data updated daily.
© 2026 AI-Buzz. Early access — data updated daily.
Open-source vector database. Scalable similarity search engine.
Founded by: Charles Xie, Xianjing Wang, Frank Liu
Metrics computed from HN discussion, GitHub activity, and funding data.
According to AI-Buzz, Milvus ranks #10 in AI Infrastructure for HN discussion share (out of 70 tracked with 1.1% of HN discussion), with 50% positive developer sentiment (8 HN comments analyzed), with 24 commits/week (declining), with 19,485,339 PyPI downloads in 30 days.
Source: https://ai-buzz.com/companies/milvus?utm_source=citation&utm_medium=referral&utm_campaign=cite_this_data
Metrics derived from public APIs (HN Algolia, GitHub, npm/PyPI). Sentiment classified by AI. See methodology for details →
Description
Open-source vector database. Scalable similarity search engine.
Estimated Company Size
51 - 100 employees
Website
milvus.ioFunding data not available for this company. AI-Buzz focuses on developer adoption data like package downloads and GitHub activity.
Founded
2019
Description
Milvus is an open-source vector database. Handles billions of vectors at scale. Used by enterprises for AI search.
Community engagement metrics that indicate developer traction and interest.
Last updated: 1 day ago
Mentions in HN discussions. Source: Hacker News Algolia API.
Sentiment analysis of Hacker News comments only. Does not include Reddit, Discord, or other platforms.
Total stars indicate project popularity and developer adoption.
Forks indicate active developer engagement and contribution interest.
Weekly commit activity indicates ongoing development momentum and team productivity.
Package download volume indicates real-world adoption and integration into production projects.
Read in-depth analysis and news about Milvus on AI-Buzz.
Browse articles on AI-BuzzAn open-source vector database designed for scalable similarity search and AI applications, handling billions of vectors efficiently.
A fully managed cloud service for Milvus, providing a robust, scalable, and secure vector database solution for enterprises without operational overhead.
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Package downloads and ecosystem metrics — 30-day window
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