We performed a comparison between KNIME and Tableau based on real PeerSpot user reviews.
Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining."Usability, and organising workflows in very neat manner. Controlling workflow through variables is something amazing."
"Stability is excellent. I would give it a nine out of ten."
"It's very convenient to write your own algorithms in KNIME. You can write it in Java script or Python transcript."
"It provides very fast problem solving and I don't need to do much coding in it. I just drag and drop."
"It is a stable solution...It is a scalable solution."
"We are able to automate several functions which were done manually. I can integrate several data sets quickly and easily, to support analytics."
"We have been able to appreciate the considerable reduction in prototyping time."
"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."
"The most valuable feature is the 3D charting."
"I like Tableau's heat maps and the storyboard. You can create data stories and tons of visuals with it, and it goes together really well. Tableau lets you manipulate the data in various ways."
"I like the solution's web version, more so than Power BI's web version. It just makes it easier to drag and drop things and to blend data on the backend. It simplifies the process."
"Tableau is highly scalable. Now that they've introduced Hyper, you can create an extract of more than 5 million rows in minutes and then do your analysis."
"We found Tableau has the quickest learning time out of the few other BI reporting tools that we have used."
"The data visualization piece is most valuable. We do ad-hoc analysis or one-time shot things, but there are things that we have to track every single day. When our management and our customers want to see how things are changing, the dashboarding provides that information. Tableau is key in providing that data on a refresh basis. We use a data blending tool that pumps the data into Tableau, and we just schedule it to run every single day. So, the automation of the data and being able to present it to people who are interested are the most valuable features."
"There is a lot of APIs available, which means that Tableau can be customized to a large extent."
"You are able to see and follow trends."
"The documentation needs a proper rework. "
"The most difficult part of the solution revolves around its areas concerning machine learning and deep learning."
"The predefined workflows could use a bit of improvement."
"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."
"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."
"If they had a more structured training model it would be very helpful."
"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."
"They should look at other vendors like Alteryx that are more user friendly and modern."
"Small multiples (a.k.a. Trellis charts) are possible only through very hacky means. Update: Still remains a challenge."
"What is happening, with so many tools coming up in the market, is that people have to continuously get educated in order to use some of the more advanced features."
"The tool's OpenAI integration was announced last year. However, it is late. Tableau is a good solution for end customers. However, there are some concerns regarding the stability and performance of its server architecture, including SaaS services. The server side appears unstable, and performance issues are noticeable, often accompanied by unclear error messages."
"The extraction, transformation and loading of data in Tableau takes a lot of time and we do not have confidence that Tableau is showing all the data we need."
"I am a BI consultant. I have worked on different reporting tools, such as Power BI and MicroStrategy. As compared to other tools, Tableau lags behind in handling huge enterprise-level data in terms of robust security and the single integrated metadata concept. When we connect to large or very big databases, then performance-wise, I sometimes found Tableau a little bit slow. It can have the single metadata concept like other tools for the reusability of the objects in multiple reports."
"The performance could be better."
"There should be stronger data modules for the platform."
"The architecture should be improved to better handle the data."
KNIME is ranked 1st in Data Mining with 50 reviews while Tableau is ranked 2nd in BI (Business Intelligence) Tools with 290 reviews. KNIME is rated 8.2, while Tableau is rated 8.4. 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 Tableau writes "Provides fast data access with in-memory extracts, makes it easy to create visualizations, and saves time". KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Weka and H2O.ai, whereas Tableau is most compared with Microsoft Power BI, Amazon QuickSight, Domo, SAS Visual Analytics and Databricks.
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.
