We performed a comparison between KNIME and SAS Analytics 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."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."
"It has allowed us to easily implement advanced analytics into various processes."
"We can deploy the solution in a cluster as well."
"Stability is excellent. I would give it a nine out of ten."
"It's a coding-less opportunity to use AI. This is the major value for me."
"We are able to automate several functions which were done manually. I can integrate several data sets quickly and easily, to support analytics."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"It allows for a user-friendly approach where you can simply drag and drop elements to create your model, which is a convenient and effective idea."
"They have provided virtually everything we have needed to accomplish our task, as well as continuously improving our accuracy."
"Modeling ones and figures, such as PROC LIFETEST, PROC LOGISTICS, PROC GPLOT. PROC FREQ and PROC MEANS, are also among the valuable features."
"The technical support is okay."
"It is able to connect to all major platforms, and all the smaller platforms that I have come across."
"It has facilitated timely analysis results with quality work and meaningful output."
"SAS Business Intelligence is well-suited for our large corporation. We have demand for scalable and reliable insights into information which is housed in our large systems."
"It has improved the level of efficacy and validity of our reports."
"It's very easy to use once you learn it."
"They could add more detailed examples of the functionality of every node, how it works and how we can use it, to make things easier at the beginning."
"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."
"One area that could be improved is increasing awareness and adoption of KNIME among organizations. Despite its capabilities, it is not as well-known as other tools. The advertising and marketing efforts to reach out to companies and universities have not been very successful."
"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 solution is inconvenient when it comes to wrangling data that includes multiple steps or features because each step or feature requires its own icon."
"The overall user experience feels unpolished. In particular: Data field type conversion is a real hassle, and date fields are a hassle; documentation is pretty poor; user community is average at best."
"KNIME could improve when it comes to large data markets."
"Compared to the other data tools on the market, the user interface can be improved."
"They could enhance the AI capabilities of the product."
"The graphing and visualization features could be enhanced, in my opinion. I would especially stress improving the visualization capabilities."
"The training for SAS Business Intelligence is often difficult to arrange. It is often cancelled due to not enough people being enrolled."
"This solution should be made more user-friendly."
"Once a SAS figure is produced one would like to modify things, such as titles, legends, and incorporate risk sets as a footer on the plots."
"There is potential for enhancement, particularly in the virtualized dashboard's capability to generate reports."
"Support at universities used to be limited, but I hear this is changing."
"One of the things that can be simplified is self-service analytics, especially for a citizen developer or a citizen data scientist."
KNIME is ranked 1st in Data Mining with 50 reviews while SAS Analytics is ranked 5th in Data Mining with 11 reviews. KNIME is rated 8.2, while SAS Analytics is rated 9.0. 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 Analytics writes "Provides comprehensive data analysis tools and functionalities, but its higher pricing and potential stability issues may present drawbacks". KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Dataiku Data Science Studio and Tableau, whereas SAS Analytics is most compared with IBM SPSS Statistics, Weka, SAS Enterprise Miner and IBM SPSS Modeler. See our KNIME vs. SAS Analytics report.
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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.
