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."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 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."
"We have a local representative who specializes in SPSS. He will help us do the PoC."
"The most valuable features of the IBM SPSS Modeler are visual programming, you don't have to write any code, and it is easy to use. 90 to 95 percent of the use cases, you don't have to fine-tune anything. If you want to do something deeper, for example, create a better neural network, then you have to go into the features and try to fine-tune them. However, the default selection which is made by the tool, it's very practical and works well."
"It helped me in that I didn't need to write them by hand, and I could get a result in one or two minutes. That helped me a lot."
"It handles large data better than the previous system that we were using, which was basically Excel and Access. We serve upwards of 300,000 parts over a 150 regions and we need to crunch a lot of numbers."
"The ease of use in the user interface is the best part of it. The ability to customize some of my streams with R and Python has been very useful to me, I've automated a few things with that."
"In the solution, I like the virtualization of data flow since it shows what goes where, which is mostly the strength of the tool."
"We have been able to appreciate the considerable reduction in prototyping time."
"The product is open-source and therefore free to use."
"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."
"Usability, and organising workflows in very neat manner. Controlling workflow through variables is something amazing."
"The solution allows for sharing model designs and model operations with other data analysts."
"I've tried to utilize KNIME to the fullest extent possible to replace Excel."
"It has allowed us to easily implement advanced analytics into various processes."
"It provides very fast problem solving and I don't need to do much coding in it. I just drag and drop."
"The time series should be improved."
"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."
"We have run into a few problems doing some entity matching/analytics."
"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 product does not have a search function for tags."
"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."
"The challenge for the very technical data scientists: It is constraining for them."
"In the last update, KNIME started hiding a lot of the nodes. It doesn't mean hiding, but you need to know what you're looking for. Before that, you had just a tree that you could click, and you could get an overview of what kind of nodes do I have. Right now, it's like you need to know which node you need, and then you can start typing, but it's actually more difficult to find them."
"Both RapidMiner and KNIME should be made easier to use in the field of deep learning."
"They should look at other vendors like Alteryx that are more user friendly and modern."
"KNIME's licensing and data management aren't as straightforward relative to Alteryx. Alteryx's tools are more sophisticated, so you need fewer to use it compared to KNIME. I think tab implementation could be easier, too."
"They could add more detailed examples of the functionality of every node, how it works and how we can use it, to make things easier at the beginning."
"The predefined workflows could use a bit of improvement."
"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."
"I've had some problems integrating KNIME with other solutions."
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 Data Science Studio 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.