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milvus-io/milvus

Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search

#Vector database
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46.5k
4.4k
331 contributors
Apache License 2.0
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Momentum

How fast milvus-io/milvus is gaining stars, and where it lands on Trendshift and GitHub Trending

Activity and trending

Stars, forks and merged pull requests each day or month, lined up with the repository's rank on Trendshift Trending

Aug 29 – Oct 28, 2026

Stars +659 in 61 days

0102030
26

Forks +148 in 61 days

0510
7

Merged PRs 814 in 61 days

0204060
46

Trendshift Trendingwhere the repository ranked each day it made the top 25

Not in the Trendshift top 25 in this period

Aug 29Sep 6Sep 14Sep 22Sep 30Oct 8Oct 16Oct 24
The left and right arrow keys step from day to day; Home and End go to the first and the last

Stars, forks, merged pull requests and Trendshift Trending rank, by day
DayStars gainedForks gainedMerged PRs
Sat, Aug 29, 2026+20+50
Sun, Aug 30, 2026+10+12
Mon, Aug 31, 2026+26+229
Tue, Sep 1, 2026+11+522
Wed, Sep 2, 2026+14+320
Thu, Sep 3, 2026+24+517
Fri, Sep 4, 2026+17+511
Sat, Sep 5, 2026+9+31
Sun, Sep 6, 2026+16+27
Mon, Sep 7, 2026+15+514
Tue, Sep 8, 2026+11+413
Wed, Sep 9, 2026+9+117
Thu, Sep 10, 2026+12+317
Fri, Sep 11, 2026+15+711
Sat, Sep 12, 2026+14+00
Sun, Sep 13, 2026+15+42
Mon, Sep 14, 2026+16+230
Tue, Sep 15, 2026+16+231
Wed, Sep 16, 2026+7+210
Thu, Sep 17, 2026+19+018
Fri, Sep 18, 2026+7+325
Sat, Sep 19, 2026+5+00
Sun, Sep 20, 2026+15+114
Mon, Sep 21, 2026+19+113
Tue, Sep 22, 2026+24+620
Wed, Sep 23, 2026+22+532
Thu, Sep 24, 2026+7+213
Fri, Sep 25, 2026+7+11
Sat, Sep 26, 2026+2+11
Sun, Sep 27, 2026+5+22
Mon, Sep 28, 2026+13+116
Tue, Sep 29, 2026+7+110
Wed, Sep 30, 2026+10+311
Thu, Oct 1, 2026+6+10
Fri, Oct 2, 2026+7+21
Sat, Oct 3, 2026+9+01
Sun, Oct 4, 2026+3+10
Mon, Oct 5, 2026+4+26
Tue, Oct 6, 2026+7+51
Wed, Oct 7, 2026+4+22
Thu, Oct 8, 2026+10+318
Fri, Oct 9, 2026+2+319
Sat, Oct 10, 2026+5+121
Sun, Oct 11, 2026+4+33
Mon, Oct 12, 2026+12+317
Tue, Oct 13, 2026+11+323
Wed, Oct 14, 2026+9+324
Thu, Oct 15, 2026+4+119
Fri, Oct 16, 2026+12+412
Sat, Oct 17, 2026+5+24
Sun, Oct 18, 2026+11+42
Mon, Oct 19, 2026+18+131
Tue, Oct 20, 2026+13+237
Wed, Oct 21, 2026+7+329
Thu, Oct 22, 2026+0+122
Fri, Oct 23, 2026+9+146
Sat, Oct 24, 2026+7+10
Sun, Oct 25, 2026+7+30
Mon, Oct 26, 2026+12+127
Tue, Oct 27, 2026+18+419
Wed, Oct 28, 2026+4+00
Total+659+148814
  • 1#1 on the list
  • 7Rank that day
  • Not trending
1

    • GitHub trending history

    Where the repository ranked on GitHub Trending, one dot for each day it was on a list

    Nov 15, 2024 – Dec 3, 2025Best #10

    #1#5#10#15#20#25
    Top 10
    Oct 2023AprOctAprOctApr
    The left and right arrow keys step from day to day; Home and End go to the first and the last

    Mentions and achievements

    Where people are talking about milvus-io/milvus, and every badge it has earned
    1. Sep 131 post

      • QUẢN LÝ HÀNG TỶ VECTOR VỚI HIỆU NĂNG CLOUD-NATIVE: MILVUS LÀ CƠ SỞ DỮ LIỆU VECTOR CHO CÁC BÀI TOÁN AI QUY MÔ LỚN

        Read full on Reddit

        r/opensourcevietnam

    2. Sep 91 post

      • 如果你想从零了解向量数据库，这四个 GitHub 项目值得按顺序看： 1. qdrant：高性能向量库加搜索引擎 过滤、载荷、云/自托管都齐，下一代 AI 检索很常见。中小到中等规模可以先用它很顺。 2. milvus：云原生，冲大规模 ANN 向量量级上去后，扩容和分布式是强项，企业级检索常被点名。 3. weaviate：对象和向量一起存 向量检索能叠结构化过滤，云原生容错，适合「语义 +…

        Read full on X, posted by @miles_mazy

        @miles_mazy · x.com

    3. 8 days earlier
    4. Sep 11 post

      • 8. Weaviate → Vector Database + RAG → Understand vector search, hybrid search, embeddings, and retrieval infrastructure. 🔗

        Read full on X, posted by @goyalshaliniuk

        @goyalshaliniuk · x.com

    5. 24 days earlier
    6. Aug 81 post

      • 折腾AI、LLM、Agent或机器学习项目的时候，有一份现成的高频工具清单能省下不少试错时间。 我整理了30个开发者真正常用的开源仓库，按功能分好了，方便按需取用。 核心开发框架 LangChain — 构建AI Agent、RAG应用和LLM工作流的首选，生态最全 → LlamaIndex — 把私有数据（文档、数据库、API）接到LLM，专攻RAG → LangGraph —…

        Read full on X, posted by @Huahuazo

        @Huahuazo · x.com

    7. 8 days earlier
    8. Jul 311 post

      • Everyone bookmarks LangChain. The part of the AI stack people actually pick wrong is the vector database. Here are the five worth knowing, and why most of you don't need a dedicated one

        Read full on Reddit

        r/WebAfterAI

    9. Jul 301 post

      • 如果你正在折腾 AI、LLM、Agent 或机器学习项目，这份清单应该能帮你少走很多弯路。GAS哥整理了30个开发者真正高频使用的开源仓库，按功能分类，方便你快速找到需要的那个。 核心开发框架 LangChain — 构建 AI Agent、RAG 应用和 LLM 工作流的首选框架，生态最完善。 → LlamaIndex — 把私有数据（文档、数据库、API）连接到 LLM，专攻 RAG 场景。…

        Read full on X, posted by @cevenif

        @cevenif · x.com

    10. 9 days earlier
    11. Jul 211 post

      • Need one retrieval layer for semantic search, full-text search, and metadata filtering? Milvus is an open-source vector database for AI engineers building RAG, semantic search, multimodal search, and…

        Read full on X, posted by @DanKornas

        @DanKornas · x.com

    12. 17 days earlier
    13. Jul 41 post

      • • Written in Go and C++ with hardware acceleration for CPU/GPU • Fully-distributed and K8s-native architecture for horizontal scaling • Supports real-time streaming updates and billions of vectors

        Read full on X, posted by @the_osps

        @the_osps · x.com

    14. 21 days earlier
    15. Jun 131 post

      • 🤖 milvus ⭐ 44,761 stars Searching billions of vectors shouldn't break your stack. Power your AI apps with a cloud-native vector database built for massive scale. 🔗 #AI #MachineLearning

        Read full on X, posted by @Marco_Ramilli

        @Marco_Ramilli · x.com

    16. 8 days earlier
    17. Jun 51 post

      • 🤖 milvus ⭐ 44,647 stars Building AI apps? Search billions of multi-modal embeddings in milliseconds with a cloud-native vector database designed for massive scale. 🔗 #AI #MachineLearning

        Read full on X, posted by @Marco_Ramilli

        @Marco_Ramilli · x.com

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