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."It has greatly improved the performance because it is standardized across the company."
"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."
"Stability-wise, it is a great tool."
"IBM Watson Studio consistently automates across channels."
"The system's ability to take a look at data, segment it and then use that data very differently."
"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 is a stable, reliable product."
"Watson Studio is very stable."
"Easy to use, stable, and powerful."
"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."
"It is very fast to develop solutions."
"The product is open-source and therefore free to use."
"It's a coding-less opportunity to use AI. This is the major value for me."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"It's a huge tool with machine learning features as well."
"Valuable features include visual workflow creation, workflow variables (parameterisation), automatic caching of all intermediate data sets in the workflow, scheduling with the server."
"The initial setup was complex."
"Some of the solutions are really good solutions but they can be a little too costly for many."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"The solution's interface is very slow at times."
"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."
"We would like to see it more web-based with more functionality."
"The main challenge lies in visibility and ease of use."
"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."
"It could input more data acquisitions from other sources and it is difficult to combine with Python."
"I would like it to have data visualitation capabilities. Today I'm still creating my own data visualtions tools to present my reports."
"Data visualization needs improvement."
"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."
"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."
"KNIME could improve when it comes to large data markets."
"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."
"The predefined workflows could use a bit of improvement."
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, Microsoft Azure Machine Learning Studio, Azure OpenAI, Google Vertex AI and Amazon Comprehend, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Weka and Dataiku Data Science Studio. See our IBM Watson Studio vs. KNIME report.
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We monitor all Data Science Platforms 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.
