opensearch-project/ml-commons
ml-commons provides a set of common machine learning algorithms, e.g. k-means, or linear regression, to help developers build ML related features within OpenSearch.
⚡ Executive Summary & Quick Facts
Authoritative Sourceml-commons is ml-commons is an open-source project written in Java: ml-commons provides a set of common machine learning algorithms, e.g. k-means, or linear regression, to help developers build ML related features within OpenSearch. ..
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), opensearch-project/ml-commons has accumulated 159 GitHub stars and 235 forks. It is written in Java, licensed under Apache-2.0, and ranks #21,409 globally. It is actively maintained with the latest commit recorded on Nov 11, 2026.”
| Repository | opensearch-project/ml-commons ↗ |
|---|---|
| Primary Category | machine learning algorithms |
| Language & Stack | Java |
| Software License | Apache-2.0 |
| Community Traction | ★ 159 stars · ⑂ 235 forks · #21,409 globally |
| Maintenance | ● Active (Last commit: Nov 11, 2026) · 571 open issues |
| Target Audience | Developers and engineering teams building with Java, seeking reliable, tested, and actively maintained tooling for production workloads. |
🛡️ Repository Maintenance & Health Audit (2026)
Health Score: 92/100 · Grade AYes, ml-commons is actively maintained. Continuous telemetry recorded the last code commit on Nov 11, 2026 (2 days ago). Supported by 159 stars and 235 community forks, this repository holds a calculated health index of 92/100, reflecting very active (commits within last 14 days) and active community feedback (571 open).
Star History
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+1
STARS · LAST 30 DAYS
1
PER DAY
#1,579
MOST-STARRED Java
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +0 | +1 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +0 | +3 | +12 |
ml-commons gained 1 stars in the last 30 days, about 1 a day, and now has 159. It is about 6 years old and has averaged roughly 27 stars a year. It ranks #1,579 among Java repositories and #21,409 across all languages on GitHubRepo.
Trending Record
29
DAYS ON TRENDING
#11550
BEST RANK
Oct 10, 2026
FIRST APPEARANCE
Active
STATUS TODAY
ml-commons has maintained a continuous presence across global trending indexes, peaking at #11550. Below is the 30-day activity profile:
💡 Overview
ml-commons is an open-source project written in Java: ml-commons provides a set of common machine learning algorithms, e.g. k-means, or linear regression, to help developers build ML related features within OpenSearch. .
Engineered for speed, consistency, and developer ease, it solves common hurdles in machine-learning-algorithms. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Java for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ git clone https://github.com/opensearch-project/ml-commons.git
cd ml-commons⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
JDK 17 or higher (OpenJDK / GraalVM)
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
ml-commons coordinates its core functionality through a modular Java pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Production System Integration
Embed ml-commons into Java backend services to handle core application logic.
CI/CD Automated Pipelines
Run automated validation, builds, and integration suites during deployments.
Developer Tooling & Workflows
Accelerate developer onboarding with pre-configured project utilities.
Open Source Extension
Fork and customize internal modules under the repository's open Apache-2.0 license.
🚀 Getting Started
Install ml-commons using your package manager: `git clone https://github.com/opensearch-project/ml-commons.git`
Initialize your project workspace or configuration file for ml-commons.
Import ml-commons into your codebase or invoke it directly from your terminal.
Execute your test suite or run `ml-commons --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Java, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
opensearch-project/ml-commons is currently ranked #21,409 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #21,353 | luxir-search/luxir | C++ | ★ 160 | Compare ↗ |
| #21,353 | preferencemodel/karotte | Python | ★ 160 | Compare ↗ |
| #21,353 | planetscale/lead | Rust | ★ 160 | Compare ↗ |
| #21,353 | TGP482/XboxXBERecomp | C++ | ★ 160 | Compare ↗ |
| #21,353 | Yamz-Labs/kyojin | Python | ★ 160 | Compare ↗ |
| #21,409 | opensearch-project/ml-commons This Project | Java | ★ 159 | |
| #21,409 | wycats/textmate | Ruby | ★ 159 | Compare ↗ |
| #21,409 | kematzy/sinatra-cache | Ruby | ★ 159 | Compare ↗ |
| #21,409 | rizqme/chain.js | JavaScript | ★ 159 | Compare ↗ |
| #21,409 | dustin/beanstalk-tools | Ruby | ★ 159 | Compare ↗ |
| #21,409 | tylerhunt/remit | Ruby | ★ 159 | Compare ↗ |
Frequently Asked Questions
What does ml-commons do? +
ml-commons provides a set of common machine learning algorithms, e.g. k-means, or linear regression, to help developers build ML related features within OpenSearch.
Is ml-commons actively maintained in 2026? +
Yes, ml-commons is actively maintained. The latest code push was recorded on Nov 11, 2026 (2 days ago). It holds a calculated Maintenance Health Score of 92/100 (A rating) with 159 stars and 571 open issues.
What language is ml-commons written in? +
The primary language is Java. Topics include: machine-learning-algorithms.
How many stars does ml-commons have? +
ml-commons has 159 stars and 235 forks on GitHub.
How does ml-commons rank among GitHub repositories? +
With 159 stars, opensearch-project/ml-commons is ranked #21,409 globally across all repositories tracked on GitHubRepo and #1,579 among Java projects.
What license is ml-commons distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
