We performed a comparison between DataRobot and RapidMiner based on real PeerSpot user reviews.
Find out what your peers are saying about Alteryx, RapidMiner, SAP and others in Predictive Analytics."We especially like the initial part of feature engineering, because feature engineering is included in most engines, but DataRobot has an excellent way of picking up the right features."
"DataRobot can be easy to use."
"The most valuable features are the Binary classification and Auto Model."
"It is easy to use and has a huge community that I can rely on for help. Moreover, it is interactive."
"Using the GUI, I can have models and algorithms drag and drop nodes."
"RapidMiner is very easy to use."
"What I like about RapidMiner is its all-in-one nature, which allows me to prepare, extract, transform, and load data within the same tool."
"The documentation for this solution is very good, where each operator is explained with how to use it."
"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."
"The most valuable feature is what the product sets out to do, which is extracting information and data."
"The business departments will love to work with DataRobot because they use the tool to investigate their data, such as targeting what they want to investigate. They don't need any data scientists near them. They can investigate at eye level and bring into the BI tool, or can bring it to the data scientist. Data scientists can use this tool to bring increase the solution to the maximum. All the others can use it, but not to the maximum."
"If we could include our existing Python or R code in DataRobot, we could make it even better. The DataRobot that we have is specific to an industry, but most of the time we would have our own algorithms, which are specific to our own use case. If we had a way by which we could integrate our proprietary things into DataRobot with a simple integration, it would help us a lot."
"I would appreciate improvements in automation and customization options to further streamline processes."
"The price of this solution should be improved."
"Many things in the interface look nice, but they aren't of much use to the operator. It already has lots of variables in there."
"I think that they should make deep learning models easier."
"RapidMiner can improve deep learning by enhancing the features."
"RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."
"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."
"Improve the online data services."
Earn 20 points
DataRobot is ranked 5th in Predictive Analytics while RapidMiner is ranked 2nd in Predictive Analytics with 19 reviews. DataRobot is rated 8.0, while RapidMiner is rated 8.6. The top reviewer of DataRobot writes "Easy to use, priced well, and can be customized". On the other hand, the top reviewer of RapidMiner writes "Offers good tutorials that make it easy to learn and use, with a powerful feature to compare machine learning algorithms". DataRobot is most compared with Amazon SageMaker, Microsoft Azure Machine Learning Studio, Datadog, Alteryx and SAS Predictive Analytics, whereas RapidMiner is most compared with KNIME, Alteryx, Dataiku Data Science Studio, Tableau and Databricks.
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We monitor all Predictive Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.