H2O Driverless AI vs Orange Data Mining
H2O Driverless AI
h2o.aiOrange Data Mining
orangedatamining.comSide by side
| Figure | H2O Driverless AI | Orange Data Mining |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | — |
| Self-hosted | Yes | — |
| Plans published | 1 | 1 |
| Spec score · Data Science and Machine Learning Platforms | 7.8 (#8) | 7.4 (#11) |
| Spec score · Low-Code Machine Learning Platforms Software | 7.9 (#9) | 7.4 (#12) |
| Spec score · Predictive Analytics Software | 7.9 (#15) | 7.6 (#17) |
| Intended users | H2O describes data scientists, DevOps and IT professionals, and business analysts as audiences for Driverless AI. | The maker describes Orange as suited to beginners and expert data scientists and says it is used in schools, universities, and professional training. |
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.
Orange Data Mining
Orange Data Mining is open-source software for machine learning, data mining, and data visualization. It runs on Linux, macOS, and Windows, and is available for free under the GNU GPL 3.0 or later; add-ons may have additional licensing requirements. Users make analyses by connecting widgets for retrieving and preparing data, visualizing it, building models, and evaluating them. Interactive views include scatter plots, box plots, histograms, heat maps, MDS projections, and model-specific displays. The model catalog includes methods such as decision trees, random forests, support vector machines, neural networks, and logistic regression. Add-ons cover areas including text mining, network analysis, fairness, time series, and gene expression analysis. Data can come from spreadsheet and text files, Google Spreadsheets, and PostgreSQL or MSSQL databases; the SQL widget supports only PostgreSQL and MSSQL. Orange is installed locally and can work offline. Embedded widgets send data to a server for computation, though the FAQ says it is not stored there. Orange cannot export workflows as Python scripts and is not compatible with R.