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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
27th
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 January 2026, in the Data Science Platforms category, the mindshare of KNIME Business Hub is 8.7%, down from 11.2% compared to the previous year. The mindshare of SAP Predictive Analytics is 0.9%, 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 Hub8.7%
SAP Predictive Analytics0.9%
Other90.4%
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.
AR
Senior Practice Manager - Head of SAP at a tech consulting company with 201-500 employees
Easy to implement, good data forecasting and reporting
This solution works for acquired data but not live, real-time data. If we connect it to a live backend system then we cannot perform predictive analytics on top of that. We have to first upload data to the cloud, manage the staging environment, and then perform the analysis. In the next release of this solution, I would like to see more automation in generating the models. The system can suggest the dimensions and measures that should be used, and pre-populate some of the information based on that. Power users would not have as much need for this, but this type of automation would be very helpful for business end-users.

Quotes from Members

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

Pros

"The ETL which helps me to collect, reformat, and load the data from multiple sources into one destination, a storage database."
"We are able to automate several functions which were done manually. I can integrate several data sets quickly and easily, to support analytics."
"It has allowed us to easily implement advanced analytics into various processes."
"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."
"It also has very good fundamental machine learning. It has decision trees, linear regression, and neural nets. It has a lot of text mining facilities as well. It's fairly fully-featured."
"There are a lot of connectors available in 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."
"We have found KNIME valuable when it comes to its visualization."
"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

"Sometimes, we needed more space to handle larger operations, especially since our machines had limited space and memory due to Kubernetes clusters."
"I would prefer to have more connectivity."
"The documentation needs a proper rework. ​"
"KNIME doesn't handle large datasets or a high number of records well."
"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."
"I would like to see better web scraping because every time I tried, it was not up to par, although you can use Python script."
"From the point of view of the interface, they can do a little bit better."
"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."
"This solution works for acquired data but not live, real-time data."
 

Pricing and Cost Advice

"KNIME Business Hub is expensive for small companies."
"KNIME assets are stand alone, as the solution is open source."
"They have different versions, but I am using the open-source one."
"KNIME is free and open source."
"It's an open-source solution."
"The price for Knime is okay."
"The price of KNIME is quite reasonable and the designer tool can be used free of charge."
"KNIME desktop is free, which is great for analytics teams. Server is well priced, depending on how much support is required."
"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...
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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.
881,114 professionals have used our research since 2012.