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."I would rate the stability of KNIME a ten out of ten."
"It can handle an unlimited amount of data, which is the advantage of using Knime."
"The product is open-source and therefore free to use."
"I was able to apply basic algorithms through just dragging and dropping."
"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."
"Since KNIME is a no-code platform, it is easy to work with."
"Clear view of the data at every step of ETL process enables changing the flow as needed."
"Key features include: very easy-to-use visual interface; Help functions and clear explanations of the functionalities and the used algorithms; Data Wrangling and data manipulation functionalities are certainly sufficient, as well as the looping possibilities which help you to automate parts of the analysis."
"The most valuable feature of Pentaho is the Tableau report."
"I use the BI Server, CDE Dashboards, Saiku, and Kettle, because these tools are very good and highly experienced."
"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 initial setup is pretty straightforward."
"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."
"We were able to install it without any assistance from tech support."
"Easy to use components to create the job."
"The documentation is lacking and it could be better."
"If they had a more structured training model it would be very helpful."
"I would prefer to have more connectivity."
"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."
"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."
"To enhance accessibility and user-friendliness, there is a need for improvements in the interface and usability of deep learning and large-scale learning languages."
"The pricing needs improvement."
"From the point of view of the interface, they can do a little bit better."
"We did not achieve the ROI. The work delivered to users had lesser value than the subscription cost."
"Version control would be a good addition."
"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."
"The repository should be improved."
"Logging capability is needed."
"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."
"Pentaho Business Analytics' user interface is outdated."
"Another concern is that Pentaho is not customizable or interactive."
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.