We performed a comparison between KNIME and SAS Enterprise Miner based on real PeerSpot user reviews.
Find out in this report how the two Data Mining solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."I was able to apply basic algorithms through just dragging and dropping."
"Overall KNIME serves its purpose and does a good job."
"Valuable features include visual workflow creation, workflow variables (parameterisation), automatic caching of all intermediate data sets in the workflow, scheduling with the server."
"There are a lot of connectors available in KNIME."
"From a user-friendliness perspective, it's a great tool."
"The solution allows for sharing model designs and model operations with other data analysts."
"This open-source product can compete with category leaders in ELT software."
"KNIME is fast and the visualization provides a lot of clarity. It clarifies your thinking because you can see what's going on with your data."
"I like the way the product visually shows the data pipeline."
"The solution is able to handle quite large amounts of data beautifully."
"Good data management and analytics."
"The solution is very good for data mining or any mining issues."
"The most valuable feature is the decision tree creation."
"he solution is scalable."
"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."
"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
"There should be better documentation and the steps should be easier."
"The license is quite expensive for us."
"The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R)."
"Compared to the other data tools on the market, the user interface can be improved."
"Data visualization needs improvement."
"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."
"It could be easier to use."
"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 ease of use can be improved. When you are new it seems a bit complex."
"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."
"The user interface of the solution needs improvement. It needs to be more visual."
"The initial setup is challenging if doing it for the first time."
"Virtualization could be much better."
"The product must provide better integration with cloud-native technologies."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"The solution is much more complex than other options."
KNIME is ranked 1st in Data Mining with 50 reviews while SAS Enterprise Miner is ranked 6th in Data Mining with 13 reviews. KNIME is rated 8.2, while SAS Enterprise Miner is rated 7.6. The top reviewer of KNIME writes "A low-code platform that reduces data mining time by linking script". On the other hand, the top reviewer of SAS Enterprise Miner writes "A stable product that is easy to deploy and can be used for structured and unstructured data mining". KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Dataiku and Weka, whereas SAS Enterprise Miner is most compared with SAS Visual Analytics, IBM SPSS Modeler, RapidMiner, Microsoft Azure Machine Learning Studio and SAS Analytics. See our KNIME vs. SAS Enterprise Miner report.
See our list of best Data Mining vendors and best Data Science Platforms vendors.
We monitor all Data Mining 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.