We performed a comparison between Cloudera Data Science Workbench and KNIME based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don't interfere with each other. The deployment of machine learning is fast and easy to manage. Its API calls are also fast."
"The Cloudera Data Science Workbench is customizable and easy to use."
"It's a very powerful and simple tool to use."
"One of the greatest advantages of KNIME is that it can be used by those without any coding experience. those with no coding background can use it."
"It is very fast to develop solutions."
"It's a coding-less opportunity to use AI. This is the major value for me."
"The ETL which helps me to collect, reformat, and load the data from multiple sources into one destination, a storage database."
"We have found KNIME valuable when it comes to its visualization."
"This open-source product can compete with category leaders in ELT software."
"I've never had any problems with stability."
"Running this solution requires a minimum of 12GB to 16GB of RAM."
"The tool's MLOps is not good. It's pricing also needs to improve."
"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."
"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'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."
"In the last update, KNIME started hiding a lot of the nodes. It doesn't mean hiding, but you need to know what you're looking for. Before that, you had just a tree that you could click, and you could get an overview of what kind of nodes do I have. Right now, it's like you need to know which node you need, and then you can start typing, but it's actually more difficult to find them."
"The most difficult part of the solution revolves around its areas concerning machine learning and deep learning."
"Compared to the other data tools on the market, the user interface can be improved."
"The ability to handle large amounts of data and performance in processing need to be improved."
"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."
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Cloudera Data Science Workbench is ranked 17th in Data Science Platforms with 2 reviews while KNIME is ranked 4th in Data Science Platforms with 50 reviews. Cloudera Data Science Workbench is rated 7.0, while KNIME is rated 8.2. The top reviewer of Cloudera Data Science Workbench writes "Useful for data science modeling but improvement is needed in MLOps and pricing ". On the other hand, the top reviewer of KNIME writes "A low-code platform that reduces data mining time by linking script". Cloudera Data Science Workbench is most compared with Databricks, Amazon SageMaker, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio and SAS Enterprise Miner, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Weka and Dataiku Data Science Studio.
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