We performed a comparison between IBM Predictive Analytics and RapidMiner based on real PeerSpot user reviews.
Find out what your peers are saying about Alteryx, RapidMiner, SAP and others in Predictive Analytics."The most valuable feature is the predictive capability in marketing use cases."
"The most valuable feature is what the product sets out to do, which is extracting information and data."
"It is easy to use and has a huge community that I can rely on for help. Moreover, it is interactive."
"The most valuable features are the Binary classification and Auto Model."
"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."
"The data science, collaboration, and IDN are very, very strong."
"RapidMiner is a no-code machine learning tool. I can install it on my local machine and work with smaller datasets. It can also connect to databases, allowing me to build models directly on the data stored there. RapidMiner offers a wider range of operators than other tools like Dataiku, making it a better option for my needs."
"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."
"Using IBM Predictive Analytics requires more skill, resources, and training than some other solutions."
"The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator."
"RapidMiner isn't cheap. It's a complete solution, but it's costly."
"In the Mexican or Latin American market, it's kind of pricey."
"The visual interface could use something like the-drag-and-drop features which other products already support. Some additional features can make RapidMiner a better tool and maybe more competitive."
"I would like to see more integration capabilities."
"The price of this solution should be improved."
"One challenge I encountered while implementing RapidMiner was the lack of documentation. Since there aren't as many users, finding resources to learn the tool was initially difficult. To overcome this hurdle, I believe RapidMiner could improve by providing more tutorials tailored for new users."
"It would be helpful to have some tutorials on communicating with Python."
Earn 20 points
IBM Predictive Analytics is ranked 22nd in Predictive Analytics while RapidMiner is ranked 2nd in Predictive Analytics with 20 reviews. IBM Predictive Analytics is rated 7.0, while RapidMiner is rated 8.6. The top reviewer of IBM Predictive Analytics writes "Good prediction capability for marketing purposes, although it needs to be more flexible". On the other hand, the top reviewer of RapidMiner writes "A no-code tool that helps to build machine learning models ". IBM Predictive Analytics is most compared with , whereas RapidMiner is most compared with KNIME, Alteryx, Dataiku, Tableau and Microsoft Azure Machine Learning Studio.
See our list of best Predictive Analytics vendors.
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.
