AutoKeras vs DataRobot
AutoKeras
autokeras.comDataRobot
datarobot.comSide by side
| Figure | AutoKeras | DataRobot |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | Yes |
| Open source | Yes | — |
| Web | — | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 1 |
| Spec score · AutoML Software | 8.9 (#2) | 7.9 (#11) |
| Purpose | AutoKeras is an AutoML system based on Keras, developed to make machine learning accessible to everyone. | DataRobot provides a platform to develop, deliver, and govern AI solutions, including agentic, generative, and predictive AI. |
| Security | The official pages opened for this research do not state security certifications or compliance claims. | DataRobot says it encrypts data in transit and at rest and supports SAML single sign-on, LDAP for Self-Managed customers, and multi-factor authentication. |
Plans
In their own words
AutoKeras
AutoKeras is a free, open-source AutoML system based on Keras, designed to make machine learning accessible through code. It supports image and text classification and regression, as well as classification and regression for structured data. Its documentation also includes a tutorial for multi-task or multimodal datasets. Users can assemble custom models from AutoKeras blocks and let the system search for detailed configurations. Image workflows can set architecture type, normalization and data augmentation, or leave those choices for automatic tuning. The best model found can be exported as a Keras Model. The Python package is installed with pip and supports Linux, macOS and Windows, including self-hosted use. The installation guide supports Python 3 and recommends PyTorch version 2.3.0 or later with the PyTorch backend. By default, the final 20% of training data is used for validation, though users can set a different split or supply validation data. Model selection uses validation loss by default, with support for customized metrics and objectives. The project directs users to GitHub Discussions for questions.
DataRobot
DataRobot is a platform for developing, delivering, and governing agentic, generative, and predictive AI solutions. Its Agent Workforce Platform supports building production agents, deploying them across infrastructure, and governing them organization-wide. Development tools include data and tool registries, a vector store, code-first workflows, and workflow evaluation and comparison. Integrations cover business applications, LLMs, APIs and frameworks, data platforms, and AI infrastructure, with documented connections to AWS, Azure, Google Cloud, and Snowflake. The platform can run on-premise, in a virtual private cloud, or as software as a service. DataRobot says it encrypts data in transit and at rest and supports SAML single sign-on, multifactor authentication, and LDAP for self-managed customers. It lists ISO 27001 and SOC 2 Type II certifications. Pricing is on request, with a 30-day trial. The trial costs nothing, allows up to five team members, and deletes data and assets 30 days after expiration unless the user contacts Sales.