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 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 very stable and reliable solution."
"Stability-wise, it is a great tool."
"IBM Watson Studio consistently automates across channels."
"It has greatly improved the performance because it is standardized across the company."
"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 system's ability to take a look at data, segment it and then use that data very differently."
"It's a very powerful and simple tool to use."
"Key features include: very easy-to-use visual interface; Help functions and clear explanations of the functionalities and the used algorithms; Data Wrangling and data manipulation functionalities are certainly sufficient, as well as the looping possibilities which help you to automate parts of the analysis."
"Easy to use, stable, and powerful."
"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 quite scalable, which is one of the most important features that we found."
"The most valuable feature is the data wrangling, which is what I mainly use it for."
"Easy to connect with every database: We use queries from SQL, Redshift, Oracle."
"What I like most about KNIME is that it's user-friendly. It's a low-code, no-code tool, so students don't need coding knowledge. You can make use of different kinds of nodes. KNIME even has a good description of each node."
"So a better user interface could be very helpful"
"The decision making in their decision making feature is less good than other options."
"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"The main challenge lies in visibility and ease of use."
"We would like to see it more web-based with more functionality."
"The initial setup was complex."
"The solution's interface is very slow at times."
"The program is not fit for handling very large files or databases (greater than 1GB); it gets too slow and has a tendency to crash easily."
"KNIME needs to provide more documentation and training materials, including webinars or online seminars."
"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."
"When deploying models on a regular system, it works fine. However, when accuracy is a priority, hyperparameter tuning is necessary. Currently, KNIME doesn't have the best tools for this which they could improve in this area."
"It's very general in terms of architecture, and as a result, it doesn't support efficient running. That is, the speed needs to be improved."
"There should be better documentation and the steps should be easier."
"KNIME is not scalable."
"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."
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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