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KNIME Business Hub vs SAP Predictive Analytics comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Nov 2, 2025

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

KNIME Business Hub
Ranking in Data Science Platforms
3rd
Average Rating
8.2
Reviews Sentiment
7.1
Number of Reviews
60
Ranking in other categories
Data Mining (1st)
SAP Predictive Analytics
Ranking in Data Science Platforms
28th
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2026, in the Data Science Platforms category, the mindshare of KNIME Business Hub is 7.5%, down from 11.4% compared to the previous year. The mindshare of SAP Predictive Analytics is 1.2%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
KNIME Business Hub7.5%
SAP Predictive Analytics1.2%
Other91.3%
Data Science Platforms
 

Featured Reviews

DG
BI Analyst at a photography company with 11-50 employees
Enables fast project development with efficient workflow modifications and promising features while offering modularity and reusability
KNIME is simple and allows for fast project development due to its reusability. I appreciate the ability to make improvements or modifications in existing workflows. Although I have not yet used the forecasting and customer profiling features, I find them promising. Another effective feature is the ability to use GET request objects to retrieve data from websites or APIs. This makes iterative steps easy to manage. It is more elastic and modern compared to SAP Data Services, allowing node creation and regrouping components or steps for reuse in different projects.
Gary Cook - PeerSpot reviewer
Executive at Empowered Analytics
Enables us to forecast and pull trends and has an easy installation
My rating for SAP Predictive Analytics would be an eight out of ten. If I have to be bold, I'll probably say that we're building away hours, and we are actually putting a lot of the actual predicting stuff back into the warehouse. So running it very bi-directionally. So I'm not sure what its integration features are at the moment, but that's an area we're going to look into in the next month or so.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"I was able to apply basic algorithms through just dragging and dropping."
"It offers a node-based data integration and processing system connected through a user-friendly drag-and-drop interface. This makes it an excellent choice for data analytics and engineering tasks."
"The product is user-friendly."
"We have been able to appreciate the considerable reduction in prototyping time."
"This solution is easy to use and it can be used to create any kind of model."
"KNIME is easy to learn."
"KNIME is more intuitive and easier to use, which is the principal advantage."
"We leverage KNIME flexibility in order to query data from our database and manipulate them for any ad-hoc business case, before presenting results to stakeholders."
"The most valuable features are the analytics and reporting."
"I think the features of the actual ability to forecast and pull trends and correlations has been really good."
 

Cons

"KNIME doesn't handle large datasets or a high number of records well."
"It could input more data acquisitions from other sources and it is difficult to combine with Python."
"I would like it to have data visualitation capabilities. Today I'm still creating my own data visualtions tools to present my reports."
"The documentation needs a proper rework. ​"
"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."
"They should look at other vendors like Alteryx that are more user friendly and modern."
"The program is not fit for handling very large files or databases (greater than 1GB); it gets too slow and has a tendency to crash easily."
"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."
"This solution works for acquired data but not live, real-time data."
 

Pricing and Cost Advice

"With KNIME, you can use the desktop version free of charge as much as you like. I've yet to hit its limits. If I did, I'd have to go to the server version, and for that you have to pay. Fortunately, I don't have to at the moment."
"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 client versions are mostly free, and we pay only for the KNIME server version. It's not a cheap solution."
"KNIME is an open-source tool, so it's free to use."
"It's an open-source solution."
"I use the open-source version."
"KNIME desktop is free, which is great for analytics teams. Server is well priced, depending on how much support is required."
"KNIME Business Hub is expensive for small companies."
"A free trial version is available for testing out this solution."
"The pricing is reasonable"
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
University
9%
Manufacturing Company
9%
Educational Organization
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business20
Midsize Enterprise16
Large Enterprise29
No data available
 

Questions from the Community

What do you like most about KNIME?
Since KNIME is a no-code platform, it is easy to work with.
What is your experience regarding pricing and costs for KNIME?
I rate the product’s pricing a seven out of ten, where one is cheap and ten is expensive.
What needs improvement with KNIME?
I have seen the potential to interact with Python, which is currently a bit limited. I am interested in the newer version, 5.4, when it becomes available. The machine learning and profileration asp...
Ask a question
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Also Known As

KNIME Analytics Platform
SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA
 

Overview

 

Sample Customers

Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
mBank
Find out what your peers are saying about KNIME Business Hub vs. SAP Predictive Analytics and other solutions. Updated: December 2025.
881,707 professionals have used our research since 2012.