Capability matrix¶
The following table provides an evolving comparison of capabilities available in DataRobot Classic and Workbench.
| DataRobot Classic | Workbench | |
|---|---|---|
| Generative AI | ||
| Add/configure vector databases | No | Yes |
| Build/Chat/Compare LLM blueprints | No | Yes |
| Evaluation and moderation metrics | No | Yes |
| Deploy LLMs | No | Yes |
| General platform features | ||
| Sharing | Data, projects | Data, Use Cases |
| Business-wide solution | No, single projects | Yes, experiments in a Use Case |
| Authentication | SSO, 2FA, API key management | SSO, 2FA, API key management |
| GPUs (for deep learning) | Yes | Yes |
| Data-related capabilities | ||
| Data sources | Certified JDBC Connectors, local file upload, URL | Snowflake, BigQuery, Databricks, S3, local file upload, AI Catalog assets |
| Data preparation | No | Wrangling |
| Feature Discovery | Yes | Yes |
| Data Quality Assessment | Yes | No |
| Data storage | AI Catalog | Data Registry |
| User-created feature lists | Yes | Yes |
| Modeling-related capabilities | ||
| Modeling types | Binary classification, multiclass classification, regression, multilabel, clustering, anomaly detection | Binary classification, multiclass classification, regression, clustering, anomaly detection |
| Partitioning | Random, Partition Feature, Group, Date/Time, Stratified | Random, Stratified, Date/Time, User-defined grouping, Automated grouping |
| TVH partitioning | Yes | Yes |
| Modeling modes | Quick, full Autopilot, Comprehensive, Manual | Quick, Manual, Comprehensive (predictive only) |
| Incremental learning | No | Yes |
| Advanced options | Yes | Partitioning, monotonic, weight, insurance-specific, geospatial |
| Time-aware | Yes, time series and OTV | Yes |
| Blenders | Yes, with option enabled | No |
| Retraining | Yes | New feature list, sample size, training period |
| Model Repository | Yes | Yes |
| Composable ML | Yes | Yes |
| Visual AI | Yes | No |
| Bias and Fairness | Yes | No |
| Text AI | Yes | Yes, for supported model types |
| Location AI | Yes | Yes |
| Model insights | See the full list | Insights for predictive or time-aware experiments |
| Prediction Explanations | XEMP and SHAP | SHAP (predictive only), XEMP if SHAP is not supported |
| Text Explanations | Yes for XEMP and SHAP | Yes for XEMP |
| Unlocking holdout | Automatically for the recommended model or anything prepared for deployment | Automatically for all models |
| Downloads | Data, Leaderboard, Scoring Code, Compliance Report, exportable charts | Compliance Report |
| Prediction-related capabilities | ||
| Predictions | Yes | Yes |
| MLOps | ||
| MLOps | Yes | Yes |
| No-Code AI Apps | ||
| No-Code AI Apps | Yes | Yes |
| DataRobot Notebooks | ||
| DataRobot Notebooks | Yes | Yes |
| Notebook scheduling | No | Yes |
| Codespaces | No | Yes |
| Notebook sharing | No | Yes |
| DataRobot Generative AI | ||
| GenAI | No | Yes |
Updated December 10, 2024
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