We performed a comparison between IBM SPSS Statistics 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."SPSS is quite robust and quicker in terms of providing you the output."
"The most valuable features are the solution is easy to use, training new users is not difficult, and our usage is comprehensive because the whole service is beneficial."
"in terms of the simplicity, I think the SPSS basic can handle it."
"The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS."
"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."
"IBM SPSS Statistics depends on AI."
"The software offers consistency across multiple research projects helping us with predictive analytics capabilities."
"Since we are using the software as a statistical tool, I would say the best aspects of it are the regression and segmentation capabilities. That said, I've used it for all sorts of things."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"It has allowed us to easily implement advanced analytics into various processes."
"Stability is excellent. I would give it a nine out of ten."
"The solution is good for teaching, since there is no need to code."
"I've never had any problems with stability."
"Since KNIME is a no-code platform, it is easy to work with."
"KNIME is easy to learn."
"It provides very fast problem solving and I don't need to do much coding in it. I just drag and drop."
"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."
"The technical support should be improved."
"One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated."
"The statistics should be more self-explanatory with detailed automated reports."
"I feel that when it comes to conducting multiple analyses, there could be more detailed information provided. Currently, the software gives a summary and an overview, but it would be beneficial to have specific details for each product or variable."
"This solution is not suitable for use with Big Data."
"Improvements are needed in the user interface, particularly in terms of user-friendliness."
"In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options."
"KNIME is not good at visualization."
"Though I can use KNIME in a 64-bit platform in the lab, it's missing some features. For example, from my laptop, I can use the image reader feature of KNIME. However, in the lab, the image reader node is missing."
"When deploying models on a regular system, it works fine. However, when accuracy is a priority, hyperparameter tuning is necessary. Currently, KNIME doesn't have the best tools for this which they could improve in this area."
"KNIME needs to provide more documentation and training materials, including webinars or online seminars."
"I would like to see better web scraping because every time I tried, it was not up to par, although you can use Python script."
"The most difficult part of the solution revolves around its areas concerning machine learning and deep learning."
"KNIME is not scalable."
"The documentation needs a proper rework. "
IBM SPSS Statistics is ranked 3rd in Data Mining with 36 reviews while KNIME is ranked 1st in Data Mining with 50 reviews. IBM SPSS Statistics is rated 8.0, while KNIME is rated 8.2. The top reviewer of IBM SPSS Statistics writes "Enhancing survey analysis that provides valued insightfulness". On the other hand, the top reviewer of KNIME writes "A low-code platform that reduces data mining time by linking script". IBM SPSS Statistics is most compared with Alteryx, TIBCO Statistica, Microsoft Azure Machine Learning Studio, IBM SPSS Modeler and MathWorks Matlab, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Dataiku and Weka. See our IBM SPSS Statistics vs. KNIME report.
See our list of best Data Mining vendors and best Data Science Platforms vendors.
We monitor all Data Mining 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.