# Capability matrix
URL: https://docs.datarobot.com/en/docs/release/deprecations-and-migrations/wb-capability-matrix.html

> An evolving comparison of capabilities available in DataRobot Classic and Workbench.

# Capability matrix (deprecated)

This table will no longer be updated, as of January 1, 2025, in recognition of the near completion of the migration to the NextGen inteface. To see feature support going forward, visit the monthly [release notes](https://docs.datarobot.com/en/docs/release/cloud-history/index.html).

| Feature | 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 |
| Application templates |  |  |
| Application templates | No | Yes |

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