We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"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."
"KNIME assets are stand alone, as the solution is open source."
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WPS is used in production on a huge range of systems at sites around the world. Thousands of analysts are using WPS in their daily data processing and analysis tasks, and thousands more rely on the heavy-lifting ability of WPS overnight and scheduled processing to deliver the information they require. Customers are able to choose to run WPS software on IBM z/OS Mainframes, servers and workstations running UNIX, Linux, Solaris, AIX, macOS and the full range of Microsoft Windows operating systems to fit in with existing or planned infrastructure.
KNIME is ranked 3rd in Data Science Platforms with 15 reviews while WPS Analytics is ranked 26th in Data Science Platforms. KNIME is rated 8.2, while WPS Analytics is rated 0.0. The top reviewer of KNIME writes "Has good machine learning and big data connectivity but the scheduler needs improvement ". On the other hand, KNIME is most compared with Alteryx, RapidMiner, Databricks, Weka and Dataiku Data Science Studio, whereas WPS Analytics is most compared with SAS Visual Analytics, Alteryx, SAS Visual Data Mining and Machine Learning, Databricks and IBM SPSS Statistics.
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We monitor all Data Science Platforms 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.