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 system's ability to take a look at data, segment it and then use that data very differently."
"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."
"It has greatly improved the performance because it is standardized across the company."
"The scalability of IBM Watson Studio is great."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"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 is a stable, reliable product."
"It has a lot of data connectors, which is extremely helpful."
"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."
"There are a lot of connectors available in KNIME."
"It's a huge tool with machine learning features as well."
"This solution is easy to use and especially good at data preparation and wrapping."
"Easy to connect with every database: We use queries from SQL, Redshift, Oracle."
"It's a very powerful and simple tool to use."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"This open-source product can compete with category leaders in ELT software."
"I think maybe the support is an area where it lacks."
"The initial setup was complex."
"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."
"I want IBM's technical support team to provide more specific answers to queries."
"We would like to see it more web-based with more functionality."
"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 main challenge lies in visibility and ease of use."
"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."
"The most difficult part of the solution revolves around its areas concerning machine learning and deep learning."
"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."
"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."
"I would prefer to have more connectivity."
"The main issue with KNIME is that it sometimes uses too much CPU and RAM when working with large amounts of data."
"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."
"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."
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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