We performed a comparison between IBM SPSS Modeler and RapidMiner based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."It's very easy to use. The drag and drop feature makes it very easy when you are building and testing the streams. That's very useful."
"Our go live process has been slightly enhanced compared to the previous programmatic process. There is now a faster time to production from the business end."
"I think it is the point and drag features that are the most valuable. You can simply click at the windows, and then pull up the functions."
"Automated modelling, classification, or clustering are very useful."
"It handles large data better than the previous system that we were using, which was basically Excel and Access. We serve upwards of 300,000 parts over a 150 regions and we need to crunch a lot of numbers."
"The supervised models are valuable. It is also very organized and easy to use."
"It works fine. I have not had any stability issues; it is always up."
"New algorithms are added into every version of Modeler, e.g., SMOTE, random forest, etc. The Derive node is used for the syntax code to derive the data."
"The most valuable features are the Binary classification and Auto Model."
"The data science, collaboration, and IDN are very, very strong."
"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."
"The documentation for this solution is very good, where each operator is explained with how to use it."
"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."
"We value the collaboration and governance features because it's a comprehensive platform that covers everything from data extraction to modeling operations in the ML language. RapidMiner is competitive in the ML space."
"I like not having to write all solutions from code. Being able to drag and drop controls, enables me to focus on building the best model, without needing to search for syntax errors or extra libraries."
"It is easy to use and has a huge community that I can rely on for help. Moreover, it is interactive."
"Requires more development."
"Regarding visual modeling, it is not the biggest strength of the product, although from what I hear in the latest release it's going to be a lot stronger. That, to me, has always been the biggest flaw in using this. It's very difficult to get good visualization."
"The challenge for the very technical data scientists: It is constraining for them."
"If IBM could add some of the popular models into the SPSS for further analysis, like popular regression models, I think that would be a helpful improvement."
"I would like better integration into the Weather Company solution. I have raised a couple of concerns about this integration and having more time series capabilities."
"I think mapping for geographic data would also be a really great thing to be able to use."
"The standard package (personal) is not supported for database connection."
"Initial setup of the software was complex, because of our own problems within the government."
"RapidMiner can improve deep learning by enhancing the features."
"I think that they should make deep learning models easier."
"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."
"The server product has been getting updated and continues to be better each release. When I started using RapidMiner, it was solid but not easy to set up and upgrade."
"The price of this solution should be improved."
"RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."
"It would be helpful to have some tutorials on communicating with Python."
"RapidMiner isn't cheap. It's a complete solution, but it's costly."
IBM SPSS Modeler is ranked 12th in Data Science Platforms with 38 reviews while RapidMiner is ranked 7th in Data Science Platforms with 19 reviews. IBM SPSS Modeler is rated 8.0, while RapidMiner is rated 8.6. The top reviewer of IBM SPSS Modeler writes "Easy to use, quick to learn, and offers many ways to analyze data". 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". IBM SPSS Modeler is most compared with KNIME, Microsoft Power BI, IBM SPSS Statistics, Alteryx and SAS Visual Analytics, whereas RapidMiner is most compared with KNIME, Alteryx, Dataiku Data Science Studio, Tableau and DataRobot. See our IBM SPSS Modeler vs. RapidMiner report.
See our list of best Data Science Platforms vendors.
We monitor all Data Science Platforms 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.
