We performed a comparison between IBM Watson Studio and KNIME based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Stability-wise, it is a great tool."
"It is a very stable and reliable solution."
"It stands out for its substantial AI capabilities, offering a broad spectrum of features for crafting solutions that meet specific requirements."
"Watson Studio is very stable."
"The scalability of IBM Watson Studio is great."
"The main benefit is the ease of use. We see a lot of engineers in our site and customers that really like the way the tools are able to work with the people."
"IBM Watson Studio consistently automates across channels."
"The solution is very easy to use."
"This solution is easy to use and it can be used to create any kind of model."
"I was able to apply basic algorithms through just dragging and dropping."
"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."
"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."
"It has allowed us to easily implement advanced analytics into various processes."
"We have been able to appreciate the considerable reduction in prototyping time."
"Stability is excellent. I would give it a nine out of ten."
"The most valuable is the ability to seamlessly connect operators without the need for extensive programming."
"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."
"I think maybe the support is an area where it lacks."
"Some of the solutions are really good solutions but they can be a little too costly for many."
"I want IBM's technical support team to provide more specific answers to queries."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"We would like to see it less as one big, massive product, but more based on smaller services that we can then roll out to consumers."
"Initially, it was quite complex. For us, it was not only a matter of getting it installed, that was just a start. It was also trying to come up with a standard way of implementing it across the entire organization, which had been a challenge."
"We would like to see it more web-based with more functionality."
"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."
"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 dynamic column name feature could be improved. When attempting to automate processes involving columns, such as with companies, it becomes difficult to achieve the same result when we make changes."
"KNIME is not good at visualization."
"KNIME's documentation is not strong."
"The documentation needs a proper rework. "
"It could input more data acquisitions from other sources and it is difficult to combine with Python."
IBM Watson Studio is ranked 10th in Data Science Platforms with 13 reviews while KNIME is ranked 4th in Data Science Platforms with 50 reviews. IBM Watson Studio is rated 8.2, while KNIME is rated 8.2. The top reviewer of IBM Watson Studio writes "A highly robust and well-documented platform that simplifies the complex world of AI". On the other hand, the top reviewer of KNIME writes "A low-code platform that reduces data mining time by linking script". IBM Watson Studio is most compared with Databricks, Azure OpenAI, Microsoft Azure Machine Learning Studio, Google Vertex AI and Amazon Comprehend, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Dataiku and Weka. See our IBM Watson Studio vs. KNIME report.
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