H2O by h2oai
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
About H2O
From the project's README at github.com/h2oai/h2o-3. Lightly cleaned for readability; for the full source see the upstream repo.
For any question not answered in this file or in H2O-3 Documentation, please use:
[](https://github.com/h2oai/h2o-3/discussions/categories/q-a) [](http://stackoverflow.com/questions/tagged/h2o) [](https://gitter.im/h2oai/h2o-3?utmsource=badge&utmmedium=badge&utmcampaign=pr-badge&utmcontent=badge)
H2O is an in-memory platform for distributed, scalable machine learning. H2O uses familiar interfaces like R, Python, Scala, Java, JSON and the Flow notebook/web interface, and works seamlessly with big data technologies like Hadoop and Spark. H2O provides implementations of many popular algorithms such as Generalized Linear Models (GLM), Gradient Boosting Machines (including XGBoost), Random Forests, Deep Neural Networks, Stacked Ensembles, Naive Bayes, Generalized Additive Models (GAM), Cox Proportional Hazards, K-Means, PCA, Word2Vec, as well as a fully automatic machine learning algorithm (H2O AutoML).
Health score breakdown
6-dimension composite. See methodology for formula and weights.
Adoption signals
Real-world usage data, pulled from each registry. The bigger the numbers, the more battle-tested the project.
| Signal | Value | Source |
|---|---|---|
| GitHub stars | 7.5k | github.com/h2oai/h2o-3 |
| GitHub forks | 2.0k | github.com/h2oai/h2o-3 |
Release & maintenance
Is this project actively maintained, or about to die? Check the recency of last commit and last release.
| Project age | 12.3 years | since Mar 2014 |
| Last commit | 2 months ago | May 4, 2026 |
| Security policy | SECURITY.md | declared by maintainers |
Self-hosting cost across providers
Detected requirements: 4GB RAM, 40GB disk minimum. Cheapest plan per provider that meets the requirement.
| Provider | Plan | Specs | Monthly | |
|---|---|---|---|---|
| hetzner | CAX11 | 2c · 4GB · 40GB | $4.13 USD | Deploy → |
| vultr | VC2 | 1c · 1GB · 25GB | $5 USD | Deploy → |
| linode | Nanode 1GB | 1c · 1GB · 25GB | $5.12 USD | Deploy → |
| digitalocean | Basic Regular 1GB | 1c · 1GB · 25GB | $6 USD | Deploy → |
Security advisories
CVE-2025-10769. Ready to self-host H2O?
Spin up a hetzner CAX11 (4GB RAM, 40GB disk) for $4.13/mo and follow the project's official install docs.
Data last refreshed Jun 21, 2026.
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