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."IBM Watson Studio consistently automates across channels."
"Stability-wise, it is a great tool."
"It is a very stable and reliable solution."
"The system's ability to take a look at data, segment it and then use that data very differently."
"Watson Studio is very stable."
"The scalability of IBM Watson Studio is great."
"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."
"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."
"It's a huge tool with machine learning features as well."
"We leverage KNIME flexibility in order to query data from our database and manipulate them for any ad-hoc business case, before presenting results to stakeholders."
"Stability is excellent. I would give it a nine out of ten."
"We have been able to appreciate the considerable reduction in prototyping time."
"This open-source product can compete with category leaders in ELT software."
"It's very convenient to write your own algorithms in KNIME. You can write it in Java script or Python transcript."
"The most useful features are the readily available extensions that speed up the work."
"I know I don't use it to its full capacity, but I love the Rule Engine feature. It has allowed me to create lookup tables on the fly and break down text fields into quantifiable data."
"I want IBM's technical support team to provide more specific answers to queries."
"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."
"We would like to see it more web-based with more functionality."
"The initial setup was complex."
"I think maybe the support is an area where it lacks."
"The main challenge lies in visibility and ease of use."
"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."
"The decision making in their decision making feature is less good than other options."
"There are a lot of tools in the product and it would help if they were grouped into classes where you can select a function, rather than a specific tool."
"It could be easier to use."
"The main issue with KNIME is that it sometimes uses too much CPU and RAM when working with large amounts of data."
"KNIME can improve by adding more automation tools in the query, similar to UiPath or Blue Prism. It would make the data collection and cleanup duties more versatile."
"They should look at other vendors like Alteryx that are more user friendly and modern."
"The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R)."
"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 is not scalable."
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.
