It's easy to do MLOps operations. It's a lot easier to manage jobs and see the logs if there's any drift in a model.
DataRobot excels in feature engineering and automates model building, simplifying MLOps operations and monitoring model performance. However, it has performance issues and is industry-specific, lacking adaptability for proprietary needs. Most users have unique algorithms and wish to integrate existing Python or R code for better efficiency. There is interest in seeing how DataRobot will support generative AI and large language models in the future.
