Hemant AddalSenior Vice President at a financial services firm
Mike TurekVice President, Business Analysis & Performance at Starboard Cruise Services
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"This open-source product can compete with category leaders in ELT software."
"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."
"This solution is easy to use and especially good at data preparation and wrapping."
"It's a coding-less opportunity to use AI. This is the major value for me."
"This solution is easy to use and it can be used to create any kind of model."
"All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"It is very fast to develop solutions."
"The most valuable feature is the ability to handle large data sets."
"The technical support is okay."
"It's very easy to use once you learn it."
"The ability to handle large amounts of data and performance in processing need to be improved."
"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 needs more examples, use cases, and MOOC to learn, especially with respect to the algorithms and how to practically create a flow from end-to-end."
"There should be better documentation and the steps should be easier."
"KNIME needs to provide more documentation and training materials, including webinars or online seminars."
"The predefined workflows could use a bit of improvement."
"The documentation is lacking and it could be better."
"There are a lot of tools in the product and it would help if they were grouped into classes where you can select a function, rather than a specific tool."
"This solution should be made more user-friendly."
"One of the things that can be simplified is self-service analytics, especially for a citizen developer or a citizen data scientist."
"The installation could also be easier, and the price could be better."
"KNIME is free as a stand-alone desktop-based platform but if you want to get a KNIME server then you can find the cost on their website."
"The price of KNIME is quite reasonable and the designer tool can be used free of charge."
"It's an open-source solution."
"The price for Knime is okay."
"At this time, I am using the free version of Knime."
"This is an open-source solution that is free to use."
"There is a Community Edition and paid versions available."
"I think that the cost-benefit ratio is okay."
"SAS is very expensive."
KNIME is ranked 1st in Data Mining with 14 reviews while SAS Analytics is ranked 6th in Data Mining with 3 reviews. KNIME is rated 8.4, while SAS Analytics is rated 9.0. The top reviewer of KNIME writes "Has good machine learning and big data connectivity but the scheduler needs improvement ". On the other hand, the top reviewer of SAS Analytics writes "A user-friendly, easy coding analytics solution that is good for typical predictive analytics". KNIME is most compared with Alteryx, RapidMiner, Databricks, Weka and Anaconda, whereas SAS Analytics is most compared with IBM SPSS Modeler, Oracle Advanced Analytics, IBM Watson Explorer, SAS Enterprise Miner and Weka. See our KNIME vs. SAS Analytics report.
See our list of best Data Mining 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.