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."The scalability of IBM Watson Studio is great."
"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."
"It has a lot of data connectors, which is extremely helpful."
"Stability-wise, it is a great tool."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"The solution is very easy to use."
"The most important thing is that it's a multi-faceted solution. It's a kind of specialist, not a generalist. It can produce very specific information for the customer. It's totally different from Google or any search engine that produces generic information. It's specialty is that it's all on video."
"It stands out for its substantial AI capabilities, offering a broad spectrum of features for crafting solutions that meet specific requirements."
"I've tried to utilize KNIME to the fullest extent possible to replace Excel."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"Easy to use, stable, and powerful."
"I was able to apply basic algorithms through just dragging and dropping."
"We have been able to appreciate the considerable reduction in prototyping time."
"I've never had any problems with stability."
"Valuable features include visual workflow creation, workflow variables (parameterisation), automatic caching of all intermediate data sets in the workflow, scheduling with the server."
"The most valuable feature is the data wrangling, which is what I mainly use it for."
"It's sometimes easy to get lost given the number of images the solution opens up when you click on the mouse and the amount of different tabs."
"The initial setup was complex."
"So a better user interface could be very helpful"
"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."
"The solution's interface is very slow at times."
"Some of the solutions are really good solutions but they can be a little too costly for many."
"I think maybe the support is an area where it lacks."
"We would like to see it more web-based with more functionality."
"Both RapidMiner and KNIME should be made easier to use in the field of deep learning."
"The data visualization part is the area most in need of improvement."
"One area that could be improved is increasing awareness and adoption of KNIME among organizations. Despite its capabilities, it is not as well-known as other tools. The advertising and marketing efforts to reach out to companies and universities have not been very successful."
"In my environment, I need to access a lot of servers with different characteristics and access methods. Some of my servers have to be accessed using proxy which is not supported by KNIME, so I still need to create the middleware to supply the source of my KNIME configurations."
"System resource usage. Knime will occupy total system RAM size and other applications will hang."
"KNIME needs to provide more documentation and training materials, including webinars or online seminars."
"They should look at other vendors like Alteryx that are more user friendly and modern."
"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."
IBM Watson Studio is ranked 11th 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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