H2O-3 vs H2O Driverless AI
H2O-3
h2o.aiH2O Driverless AI
h2o.aiSide by side
| Figure | H2O-3 | H2O Driverless AI |
|---|---|---|
| Price from | — | — |
| Free plan | — | — |
| Free trial | — | Yes |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 0 | 1 |
| Spec score · Data Science and Machine Learning Platforms | 5.7 (#22) | 7.8 (#8) |
| Spec score · Predictive Analytics Software | 5.8 (#34) | 7.9 (#15) |
| Spec score · AutoML Software | 5.7 (#28) | 7.8 (#14) |
| Spec score · Augmented Analytics Software | 5.9 (#32) | 8.0 (#12) |
| Founded | 2012 | 2012 |
| Headquarters | Mountain View, California, United States | Mountain View, California, United States |
Plans
In their own words
H2O Driverless AI
H2O Driverless AI automates machine-learning work from feature engineering and model building through validation, tuning, selection, visualization, interpretability, and scoring-pipeline generation. It explains model output at both global and individual-prediction levels. Models can be deployed as REST endpoints, cloud services, or optimized Java code for edge devices. Supported hardware includes NVIDIA GPUs, IBM Power 9, and Intel x86 CPUs; GPU-accelerated algorithms include XGBoost, TensorFlow, and LightGBM. Documented integrations include Kubernetes, Kubeflow, SageMaker, Alteryx, Jupyter/Python, KDB, Qlik, Trifacta, and UiPath. Data sources include HDFS, Amazon S3, Azure Blob Storage, Google BigQuery, Google Cloud Storage, Snowflake, JDBC, Databricks, and Delta Table. Cloud installation options are H2O AI Cloud, AWS, Azure, and Google Cloud. H2O offers a 21-day public-cloud evaluation license and a guided two-hour cloud test drive. Commercial licensing requires contacting sales; no price is listed. The default installation disables security, so production use calls for secure installation.