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 have full control of the data handling process."
"It is very scalable for non-technical people."
"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."
"Automated modelling, classification, or clustering are very useful."
"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."
"It’s definitely scalable, it’s all on the same platform, it’s well integrated. I think the integration is important in terms of scalablility because essentially, having the entire suite helps a lot to scale it"
"Some basic form of feature engineering for classification models. This really quickens the model development process."
"We had an IBM Guardium service contract where we used one of their resources to help us develop our prototype. It was a good experience, but they were helpful and responsive."
"The most valuable feature is the data wrangling, which is what I mainly use it for."
"There are a lot of connectors available in KNIME."
"I would rate the stability of KNIME a ten out of ten."
"It's a huge tool with machine learning features as well."
"Stability is excellent. I would give it a nine out of ten."
"It also has very good fundamental machine learning. It has decision trees, linear regression, and neural nets. It has a lot of text mining facilities as well. It's fairly fully-featured."
"It's very convenient to write your own algorithms in KNIME. You can write it in Java script or Python transcript."
"The visual workflow tools for custom and complex tasks always beat raw coding languages with the agility, speed to deliver, and ease of subsequent changes."
"C&DS will not meet our scalability needs."
"I think mapping for geographic data would also be a really great thing to be able to use."
"The time series should be improved."
"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."
"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."
"Initial setup of the software was complex, because of our own problems within the government."
"The forecasting could be a bit easier."
"It would be helpful if SPSS supported open-source features, for example, embedding R or Python scripts in SPSS Modeler."
"Compared to the other data tools on the market, the user interface can be improved."
"It could be easier to use."
"System resource usage. Knime will occupy total system RAM size and other applications will hang."
"If they had a more structured training model it would be very helpful."
"The program is not fit for handling very large files or databases (greater than 1GB); it gets too slow and has a tendency to crash easily."
"The most difficult part of the solution revolves around its areas concerning machine learning and deep learning."
"Data visualization needs improvement."
"I would like it to have data visualitation capabilities. Today I'm still creating my own data visualtions tools to present my reports."
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, RapidMiner, IBM SPSS Statistics, Alteryx and SAS Visual Analytics, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Dataiku 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.