We performed a comparison between IBM SPSS Modeler and KNIME based on real PeerSpot user reviews.
Find out in this report how the two Data Mining solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."We are using it either for workforce deployment or to improve our operations."
"You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after."
"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."
"It will scale up to anything we need."
"It continues to be a very flexible platform, so that it handles R and Python and other types of technology. It seems to be growing with additional open-source movement out there on different platforms."
"Some basic form of feature engineering for classification models. This really quickens the model development process."
"A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly."
"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."
"There are a lot of connectors available in KNIME."
"This open-source product can compete with category leaders in ELT software."
"Usability, and organising workflows in very neat manner. Controlling workflow through variables is something amazing."
"Since KNIME is a no-code platform, it is easy to work with."
"It allows for a user-friendly approach where you can simply drag and drop elements to create your model, which is a convenient and effective idea."
"We are able to automate several functions which were done manually. I can integrate several data sets quickly and easily, to support analytics."
"We have found KNIME valuable when it comes to its visualization."
"KNIME is easy to learn."
"Formula writing is not straightforward for an Excel user. Totally new set of functions, which takes time to learn and teach."
"Neural networks are quite simple, and now neural networks are evolving to these architecture related to deep learning, etc. They didn't incorporate this in IBM SPSS Modeler."
"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."
"Expensive to deploy solutions. You need to buy an extra deployment unit."
"We would like to see better visualizations and easier integration with Cognos Analytics for reporting."
"The challenge for the very technical data scientists: It is constraining for them."
"I understand that it takes some time to incorporate some of the new algorithms that have come out in the last few months, in the literature. For example, there is an algorithm based on how ants search for food. And there are some algorithms that have now been developed to complement rules. So that's one of the things that we need to have incorporated into it."
"It is very good, but slow. The slowness may be because we have not finalized all the background information in SPSS. It still needs some tweaking."
"Both RapidMiner and KNIME should be made easier to use in the field of deep learning."
"The ability to handle large amounts of data and performance in processing need to be improved."
"The solution is inconvenient when it comes to wrangling data that includes multiple steps or features because each step or feature requires its own icon."
"It's pretty straightforward to understand. So, if you understand what the pipeline is, you can use the drag-and-drop functionality without much training. Doing the same thing in Python requires so much more training. That's why I use KNIME."
"The license is quite expensive for us."
"The most difficult part of the solution revolves around its areas concerning machine learning and deep learning."
"System resource usage. Knime will occupy total system RAM size and other applications will hang."
"It could be easier to use."
IBM SPSS Modeler is ranked 4th in Data Mining with 38 reviews while KNIME is ranked 1st in Data Mining with 50 reviews. IBM SPSS Modeler is rated 8.0, while KNIME is rated 8.2. 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 KNIME writes "A low-code platform that reduces data mining time by linking script". IBM SPSS Modeler is most compared with Microsoft Power BI, IBM SPSS Statistics, RapidMiner, Alteryx and SAS Visual Analytics, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Dataiku and Databricks. See our IBM SPSS Modeler vs. KNIME report.
See our list of best Data Mining vendors and best Data Science Platforms vendors.
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KNIME. It free, open-source, and you can plug in Java, Python, R, and Matlab. The community is awesome.
I used IBM Modeler several years ago and found it to be effective, but expensive. Fortunately, it was for a commercially funded contract.
For KNIME I have only used it for experimental purposes and found it rather cumbersome but powerful. It is also more cost-effective.
I found RapidMiner more intuitive to learn. However, there is so much choice nowadays that it is difficult to be definitive. In my experience, it largely depended on the quality of the add-on extensions. Clearly, though, at least in universities, the cost is a significant factor.
I am not familiar with KNIME, but the main difference is KNIME is open-source and free.