H2O.ai vs Databricks Mosaic AI
A side-by-side look at scores, pricing and features — with RECATOOLS' ASEAN-aware verdict for each.
H2O.ai
Apache-2.0 AutoML core, with a paid enterprise stack for private gener...
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Databricks Mosaic AI
Build and serve models next to your lakehouse data
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| RECATOOLS Score | 7.2 / 10 | 7.3 / 10 |
| Capability | — | — |
| Value for money | — | — |
| Ease of use | — | — |
| ASEAN readiness | — | — |
| API quality | — | — |
| Pricing | Freemium | Paid |
| Free tier | Free — H2O-3 open-source core, self-hosted, no restrictions | 14-day trial with $400 usage credit; a no-cost 'Free Edition' also available via email signup |
| Paid from | Free core; commercial (Driverless AI/h2oGPTe) from ~$60K/yr custom quote | DBU-based, from ~$0.07-0.08/DBU for model serving |
| Has API | ✓ | ✓ |
| Open source | ✓ | ✗ |
| Free to use | ✓ | ✗ |
| Users | 20,000+ global organizations, 1M+ data scientists | — |
| Founded | 2012 | 2013 |
| Maker | Sri Ambati, Cliff Click, Arno Candel | Databricks, Inc. (from MosaicML, acquired 2023) |
| Verdict | The open-source half is the real draw. H2O-3 gives you distributed gradient boosting, GLMs, stacked ensembles and a solid AutoML routine under Apache 2.0, no usage cap, run it on your own hardware forever. Reviewers cons... |
Mosaic AI's whole argument is data gravity: train, fine-tune, and serve models where your data already lives instead of exporting it to a separate AI platform. It's the generative-AI layer of the Databricks lakehouse — M... |
| Full review → | Full review → |
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Comparisons cover up to 4 tools. Scores are RECATOOLS editorial assessments; verify current pricing on each vendor's site.