Alteryx Designer vs H2O Driverless AI
Alteryx Designer
alteryx.comH2O Driverless AI
h2o.aiSide by side
| Figure | Alteryx Designer | H2O Driverless AI |
|---|---|---|
| Price from | $250/mo | — |
| Free plan | — | — |
| Free trial | Yes | Yes |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 4 | 1 |
| Spec score · Augmented Analytics Software | 8.5 (#3) | 8.0 (#12) |
| Integrations | The product page says Designer integrates with 80+ data sources and outputs to over 70 tools, with native cloud connectors such as Snowflake and Databricks. | Documented integrations include Kubernetes, Kubeflow, SageMaker, Alteryx, Jupyter/Python, KDB, Qlik, Trifacta, and UiPath. |
Plans
Alteryx Designer
- Starter Edition$250 a month
- Starter EditionPriced on request
- Professional EditionPriced on request
- Enterprise EditionPriced on request
In their own words
Alteryx Designer
Alteryx Designer brings data preparation, blending, and predictive, statistical, and spatial analytics into a visual workflow environment. Users arrange drag-and-drop tools on a canvas that records each analysis step; the product page describes more than 300 automation tools. Its low-code and no-code capabilities cover spatial and prescriptive analytics, as well as extracting insights from PDFs, text files, and images. Ask Alteryx can build workflows from natural-language requests, and the AI Tool Palette can add LLMs to workflows. The product page lists connections to more than 80 data sources and outputs to over 70 tools, including cloud connectors such as Snowflake and Databricks. SDKs let users add custom tools and formulas using multiple programming languages. Designer Desktop requires Windows; macOS use is listed through a virtual machine. A separate Designer Cloud runs in a browser with current Chrome, Edge, or Firefox. Starter Edition costs $250 a month, billed annually, for 1–10 seats, cloud-only use, and CSV, XLSX, and JSON file sources.
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.