We performed a comparison between KNIME and Pentaho Business Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining."It is a stable solution...It is a scalable solution."
"It's very convenient to write your own algorithms in KNIME. You can write it in Java script or Python transcript."
"From a user-friendliness perspective, it's a great tool."
"Easy to connect with every database: We use queries from SQL, Redshift, Oracle."
"Overall KNIME serves its purpose and does a good job."
"KNIME is fast and the visualization provides a lot of clarity. It clarifies your thinking because you can see what's going on with your data."
"Easy to use, stable, and powerful."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"I use the BI Server, CDE Dashboards, Saiku, and Kettle, because these tools are very good and highly experienced."
"We were able to install it without any assistance from tech support."
"The initial setup is pretty straightforward."
"Pentaho Business Analytics' best features include the ease of developing data flows and the wide range of options to connect to databases, including those on the cloud."
"The most valuable feature of Pentaho is the Tableau report."
"Pentaho is an analytics platform that can be used when an organization has a lot of big data storage systems already installed and needs to manage and analyze that data. It has a specific use case for unstructured data, such as documents, and needs to be able to search and analyze it."
"Easy to use components to create the job."
"It's very general in terms of architecture, and as a result, it doesn't support efficient running. That is, the speed needs to be improved."
"System resource usage. Knime will occupy total system RAM size and other applications will hang."
"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."
"The documentation is lacking and it could be better."
"Not just for KNIME, but generally for software and analyzing data, I would welcome facilities for analyzing different sorts of scale data like Likert scales, Thurstone scales, magnitude ratio scales, and Guttman scales, which I don't use myself."
"It could input more data acquisitions from other sources and it is difficult to combine with Python."
"The ability to handle large amounts of data and performance in processing need to be improved."
"The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R)."
"Version control would be a good addition."
"Another concern is that Pentaho is not customizable or interactive."
"The repository should be improved."
"Pentaho, at the general level, should greatly improve the easy construction of its dashboards and easy integration of information from different sources without technical user intervention."
"Pentaho Business Analytics' user interface is outdated."
"Deployment is not simple. It is not simple because we are dealing with a lot of data; we are dealing with a lot of storage. So, it's not a simple process."
"We did not achieve the ROI. The work delivered to users had lesser value than the subscription cost."
"Logging capability is needed."
KNIME is ranked 1st in Data Mining with 50 reviews while Pentaho Business Analytics is ranked 21st in BI (Business Intelligence) Tools with 42 reviews. KNIME is rated 8.2, while Pentaho Business Analytics is rated 8.0. 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 Pentaho Business Analytics writes "Flexible, easy to understand, and simple to set up". KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Weka and Anaconda, whereas Pentaho Business Analytics is most compared with Microsoft Power BI, Databricks, Microsoft SQL Server Reporting Services, SAP Crystal Reports and Knowage.
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.