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."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."
"I think the code modeling features are the most valuable and without the need to write a code back with many different possibilities to choose from. And the second one is linked to the activity of the data preparation."
"It works fine. I have not had any stability issues; it is always up."
"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."
"Extremely easy to use, it offers a generous selection of proprietary machine learning algorithms."
"A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly."
"IBM was chosen because of usability. It's point and click, whereas the other out-of-the box-solution, or open-source solutions, require full-on programming and a much higher skill level."
"Compared to other tools, the product works much easier to analyze data without coding."
"The product is very easy to understand even for non-analytical stakeholders. Sometimes we provide them with KNIME workflows and teach them how to run it on their own machine."
"It has allowed us to easily implement advanced analytics into various processes."
"I would rate the stability of KNIME a ten out of ten."
"It's very convenient to write your own algorithms in KNIME. You can write it in Java script or Python transcript."
"This solution is easy to use and it can be used to create any kind of model."
"Automation is most valuable. It allows me to automatically download information from different sources, and once I create a workflow, I can apply it anytime I want. So, there is efficiency at the same time."
"KNIME is fast and the visualization provides a lot of clarity. It clarifies your thinking because you can see what's going on with your data."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"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."
"It is not integrated with Qlik, Tableau, and Power BI."
"It would be helpful if SPSS supported open-source features, for example, embedding R or Python scripts in SPSS Modeler."
"C&DS will not meet our scalability needs."
"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."
"I can say the solution is outdated."
"When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing."
"The data visualization part is the area most in need of improvement."
"It could input more data acquisitions from other sources and it is difficult to combine with Python."
"They should look at other vendors like Alteryx that are more user friendly and modern."
"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."
"One thing to consider is that the prebuilt nodes may not always be a perfect fit for your specific needs, although most of the time, they work quite well."
"The pricing needs improvement."
"System resource usage. Knime will occupy total system RAM size and other applications will hang."
"The documentation is lacking and it could be better."
IBM SPSS Modeler is ranked 4th in Data Mining with 6 reviews while KNIME is ranked 1st in Data Mining with 22 reviews. IBM SPSS Modeler is rated 8.0, while KNIME is rated 8.2. The top reviewer of IBM SPSS Modeler writes "Useful visual programming, minimal configuration required, and overall powerful". On the other hand, the top reviewer of KNIME writes "Allows you to easily tidy up your data, make lots of changes internally, and has good machine learning". IBM SPSS Modeler is most compared with Microsoft Power BI, RapidMiner, IBM SPSS Statistics, Alteryx and Microsoft Azure Machine Learning Studio, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Weka and Microsoft Azure Machine Learning Studio. See our IBM SPSS Modeler vs. KNIME report.
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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.