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."This open-source product can compete with category leaders in ELT software."
"From a user-friendliness perspective, it's a great tool."
"The most valuable is the ability to seamlessly connect operators without the need for extensive programming."
"We have been able to appreciate the considerable reduction in prototyping time."
"It can handle an unlimited amount of data, which is the advantage of using Knime."
"The product is very easy to understand even for non-analytical stakeholders. Sometimes we provide them with KNIME workflows and teach them how to run it on their own machine."
"What I like most about KNIME is that it's user-friendly. It's a low-code, no-code tool, so students don't need coding knowledge. You can make use of different kinds of nodes. KNIME even has a good description of each node."
"KNIME is easy to learn."
"Tableau's most valuable feature is its ability to connect with various data sources and display real-time data on three different dashboards."
"The solution deployment was straightforward."
"One of the most valuable features is that the solution allows users to build interactive dashboards. This allows the end user to modify the criteria or the filtering if need be. As far as for my personal use as a QA Engineer, I really value how extensive their API document support has been."
"The action feature which Tableau has is very useful for us. If we click on one visualization, it will pass the value to another visualization. That interactivity within different visualizations is the most valuable feature of Tableau."
"It gives us a new dimension to the way that we analyse our data."
"The maps and colors and interface are all fantastic."
"I have found Tableau easy to use and the features are superb."
"The most valuable feature is the 3D charting."
"Though I can use KNIME in a 64-bit platform in the lab, it's missing some features. For example, from my laptop, I can use the image reader feature of KNIME. However, in the lab, the image reader node is missing."
"It's pretty straightforward to understand. So, if you understand what the pipeline is, you can use the drag-and-drop functionality without much training. Doing the same thing in Python requires so much more training. That's why I use KNIME."
"When deploying models on a regular system, it works fine. However, when accuracy is a priority, hyperparameter tuning is necessary. Currently, KNIME doesn't have the best tools for this which they could improve in this area."
"Data visualization needs improvement."
"In my environment, I need to access a lot of servers with different characteristics and access methods. Some of my servers have to be accessed using proxy which is not supported by KNIME, so I still need to create the middleware to supply the source of my KNIME configurations."
"There are some parameters that I would like to have at a bigger scale. The upper limit of one node that tries to find spots or areas in photos was too small for us. It would need to be bigger."
"It could be easier to use."
"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."
"The setup was easy but we are having some problems with the configuration that is taking a long time. We have done some initial tests and some of the delays could be from bandwidth issues. However, the whole installation process should be simplified."
"The forecasting feature in Tableau in my view is too limited because it must have dates but I should be able to predict the outcome of an event without having a date as part of the input."
"Requires a lot of user training."
"From the developer perspective, the data connection handling the target data set is what most needs to be improved."
"They need to improve the icons and the filters, because they look too old, resembling Excel from 1997."
"The ability to use it on MAC machines. As far as I know, this is not possible."
"I would like them to include the Italian language, as I can see there are other foreign language in the product."
"It's already using 32 gigabytes of memory, but the performance is not so good. It's very heavy."
KNIME is ranked 1st in Data Mining with 50 reviews while Tableau is ranked 2nd in BI (Business Intelligence) Tools with 293 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, Dataiku 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.
