DataRobot features a massively parallel modeling engine that can scale to hundreds or even thousands of powerful servers to explore, build, and tune enterprise AI models. Large datasets? Wide datasets? No problem. Modeling speed and scalability is limited only by the compute resources at DataRobot's disposal.

DataRobot employs the most cutting-edge data security protocols, including LDAP, Kerberos, and SSO/SAML 2.0 for user authentication to prevent unauthorized access to proprietary data. Data sent to be trained or scored is encrypted and transmitted with TLS 1.2 over your private network to the application or prediction endpoints.

DataRobot can be installed as a service on YARN in Hadoop clusters, and perform distributed model scoring on data stored on HDFS, to bring enterprise AI to your Hadoop stack. Using Spark for large-scale data processing, DataRobot adheres to all Hadoop management processes and policies.

If your data is subject to strict regulatory compliance (such as HIPAA) or has a classification that requires specific security controls, DataRobot can be installed in an off-network configuration. Downloadable scoring code (or scoring code approximations) can be deployed to offline servers for local scoring.