No more typing reviews! Try our Samantha, our new voice AI agent.

IBM SPSS Modeler vs SAP Predictive Analytics [EOL] comparison

IBM and SAP are both solutions in the Data Science Platforms category. IBM is ranked #13 with an average rating of 8.0, while SAP is ranked #27. IBM holds a 3.2% mindshare in Data Science Platforms, compared to SAP’s 1.4% mindshare. Additionally, 86% of IBM users are willing to recommend the solution, compared to 100% of SAP users who would recommend it.
IBM SPSS Modeler
Read 40 IBM SPSS Modeler reviews
  • 3,108 Views
  • 2,331 Comparison Views
86% willing to recommend
SAP Predictive Analytics [EOL]
Read 3 SAP Predictive Analytics [EOL] reviews
  • 783 Views
  • 775 Comparison Views
100% willing to recommend
 

Comparison Buyer's Guide

Download the report
Executive SummaryUpdated on Apr 15, 2026

IBM SPSS Modeler and SAP Predictive Analytics [EOL] compete in the realm of predictive analytics. IBM SPSS Modeler has an advantage in ease of use and cost-effectiveness, while SAP Predictive Analytics [EOL] stands out for its features and integration capabilities.

Features: IBM SPSS Modeler is valued for intuitive data mining capabilities, offering automated analytics, flexible deployment options, and advanced algorithm support. SAP Predictive Analytics [EOL] provides automated predictive modeling, strong integration with SAP HANA, and is ideal for large-scale enterprise applications.

Ease of Deployment and Customer Service: IBM SPSS Modeler offers straightforward deployment with robust support, making it accessible for varying technical expertise. SAP Predictive Analytics [EOL] has a more complex deployment process due to its enterprise-level capabilities but benefits from its integration with SAP systems.

Pricing and ROI: IBM SPSS Modeler is noted for cost-effectiveness, offering compelling ROI and flexible pricing models. SAP Predictive Analytics [EOL] entails higher initial costs but delivers substantial ROI for enterprises needing comprehensive integrated solutions.

DOWNLOAD THE COMPLETE REPORT
To learn more, read our detailed Data Science Platforms Report (Updated: April 2026).
Buyer's Guide
Data Science Platforms
April 2026
Download the complete report
Helped 886,932 peers since 2012

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

IBM SPSS Modeler
Ranking in Data Science Platforms
13th
Average Rating
8.0
Reviews Sentiment
6.3
Number of Reviews
40
Ranking in other categories
Data Mining (3rd)
SAP Predictive Analytics [EOL]
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 April 2026, in the Data Science Platforms category, the mindshare of IBM SPSS Modeler is 3.2%, up from 2.3% compared to the previous year. The mindshare of SAP Predictive Analytics [EOL] is 1.4%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
IBM SPSS Modeler3.2%
SAP Predictive Analytics1.4%
Other95.4%
Data Science Platforms
 

Featured Reviews

RB
Prof. Dr. Rudolf Bisping
Business Owner at SASS GmbH
Support and flexibility enable effective project initiation and meet customer needs but deployment requires enhancement
The customer comes to you and says they want to deploy it and make a production out of this, which is very difficult and expensive with IBM SPSS Modeler. With MATLAB, there is no problem. I have a solution, and then I convert my MATLAB solution to C programming language. This I can deploy, and I can check it, and it is MISRA compatible. It is very easy to deploy it, to go from MATLAB to C or C++, which is actually needed in the car industry. In the car industry, they want to have it in the hardware. You cannot put MATLAB or IBM SPSS Modeler in the hardware of a car, but with C, there is no problem with a microcontroller. They can shoot it into the microcontroller, and I can check it with Polyspace, and it is MISRA compatible, which is an industrial standard. There is nothing similar in IBM SPSS Modeler. I made solutions with IBM SPSS Modeler, and then the customer said they wanted to make a production out of it, and it was not possible. I stopped with IBM SPSS Modeler 18. It is now 18.6 from what I know at the moment. I do not believe that there is a possibility to design a graphic user interface with it. It is itself a graphic user interface, where you put all sorts of little icons into the display.
Read full review
Gary Cook - PeerSpot reviewer
Gary Cook
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.
Read full review

Quotes from Members

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

Pros

"So far, the stability has been rock solid."
"I like the automation and that this product is very organized and easy to use."
"It is a great product for running statistical analysis."
"I think the code modeling features are the most valuable and without the need to write a code back with many different possibilities to choose from. And the second one is linked to the activity of the data preparation."
"Our business units' capabilities with SPSS Modeler is high. They no longer waste time on modeling and algorithms, meaning they are not coding any more."
"We are creating models and putting them into production much faster than we would if we had just gone with a strict, code-based solution, like R or Python."
"The software is robust with advance statistical tools in hand from time series analysis to logistic regression, it can be used by banks for fraud detection, by convenience stores for market basket analysis, for cluster analysis on customer segmentation."
"I think it is the point and drag features that are the most valuable. You can simply click at the windows, and then pull up the functions."
More IBM SPSS Modeler pros
"The most valuable features are the analytics and reporting."
"SAP Predictive Analytics is better suited for business users because it hides the complexity of the model, whereas Microsoft Azure Machine Learning provides a lot more flexibility for technical professionals to tweak the model."
"I think the features of the actual ability to forecast and pull trends and correlations has been really good."
"We always purchase SAP support because it is very good."
"I have found that the solution is very stable."
 

Cons

"The challenge for the very technical data scientists: It is constraining for them.​"
"I can say the solution is outdated."
"It is very good, but slow. The slowness may be because we have not finalized all the background information in SPSS."
"Formula writing is not straightforward for an Excel user. Totally new set of functions, which takes time to learn and teach."
"The software is quite expensive and IBM is currently marketing its other digital dashboard tools such as IBM cognos, now we aren't sure on the plans of IBM integrating these two softwares."
"When I do clustering, I want to try a different stream, but currently the only thing that I can really pick is averaging."
"I would like see more programming languages added, like MATLAB. That would be better."
"There are performance issues. Extracting data from many combined tables can take hours and occasionally crash the server due to memory leaks. This performance problem bothers people. The performance issue seems to be related to the server. We design streams on the client and submit them to the server, which generates a large SQL statement. There are two potential bottlenecks: one in the server and another in data extraction. I'm unsure about the exact mechanics of data splitting when fetching from the database."
More IBM SPSS Modeler cons
"This solution works for acquired data but not live, real-time data."
"This solution works for acquired data but not live, real-time data."
"The license fee appears to be prohibitively expensive and overly secretive, leading our clients to opt for cloud-based solutions that only charge for data storage and processing time."
 

Pricing and Cost Advice

"Its price is okay for a company, but for personal use, it is considered somewhat expensive."
"It got us a good amount of money with quick and efficient modeling."
"It is a huge increase to time savings."
"It is an expensive product."
"The scalability was kind of limited by our ability to get other people licenses, and that was usually more of a financial constraint. It's expensive, but it's a good tool."
"I am using the free version of IBM SPSS Modeler, it is the educational edition version."
"Having in mind all four tools from Garner’s top quadrant, the pricing of this tool is competitive and it reflects the quality that it offers."
"This tool, being an IBM product, is pretty expensive."
More IBM SPSS Modeler pricing and cost advice
"The pricing is reasonable"
"A free trial version is available for testing out this solution."
report
See which vendors are best for you
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
See recommendations
886,932 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
10%
Government
10%
University
8%
Outsourcing Company
7%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise4
Large Enterprise32
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for IBM SPSS Modeler?
The government has funds and a budget, it's hard to say if it's expensive or cheap. In Canada, they have a yearly budget. They used to encourage people to use the modeler for development. If ten us...
See all answers
What needs improvement with IBM SPSS Modeler?
The customer comes to you and says they want to deploy it and make a production out of this, which is very difficult and expensive with IBM SPSS Modeler. With MATLAB, there is no problem. I have a ...
See all answers
What is your primary use case for IBM SPSS Modeler?
I have been using IBM SPSS Modeler for a long time. I am using IBM SPSS Modeler mainly for ETL. Sometimes I use it to compare the results of the modeling as compared to MATLAB. MATLAB is the main t...
See all answers
Ask a question
Earn 20 points
 

Comparisons

IBM SPSS Statistics vs IBM SPSS Modeler Logo
IBM SPSS Statistics vs IBM SPSS Modeler
Compared 36% of the time
KNIME Business Hub vs IBM SPSS Modeler Logo
KNIME Business Hub vs IBM SPSS Modeler
Compared 5% of the time
Microsoft Power BI vs IBM SPSS Modeler Logo
Microsoft Power BI vs IBM SPSS Modeler
Compared 4% of the time
SAS Enterprise Miner vs IBM SPSS Modeler Logo
SAS Enterprise Miner vs IBM SPSS Modeler
Compared 4% of the time
Alteryx vs IBM SPSS Modeler Logo
Alteryx vs IBM SPSS Modeler
Compared 3% of the time
More IBM SPSS Modeler Competitors
KNIME Business Hub vs SAP Predictive Analytics [EOL] Logo
KNIME Business Hub vs SAP Predictive Analytics [EOL]
Compared 8% of the time
Saturn Cloud vs SAP Predictive Analytics [EOL] Logo
Saturn Cloud vs SAP Predictive Analytics [EOL]
Compared 7% of the time
IBM SPSS Statistics vs SAP Predictive Analytics [EOL] Logo
IBM SPSS Statistics vs SAP Predictive Analytics [EOL]
Compared 7% of the time
Starburst Galaxy vs SAP Predictive Analytics [EOL] Logo
Starburst Galaxy vs SAP Predictive Analytics [EOL]
Compared 6% of the time
Altair RapidMiner vs SAP Predictive Analytics [EOL] Logo
Altair RapidMiner vs SAP Predictive Analytics [EOL]
Compared 6% of the time
More SAP Predictive Analytics [EOL] Competitors
 

Product Reports

Buyer's Guide
IBM SPSS Modeler
April 2026
IBM SPSS Modeler reportDownload IBM SPSS Modeler product report
Buyer's Guide
Data Science Platforms
April 2026
SAP Predictive Analytics [EOL] reportDownload SAP Predictive Analytics [EOL] product report
 

Also Known As

SPSS Modeler
SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA
 

Overview

IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.

Buy
https://www.ibm.com/products/spss-modeler/pricing
 
Sign up for the trial
https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947


IBM

SAP Predictive Analytics [EOL] offered a powerful platform for creating predictive models that supported business decision-making by utilizing historical data to anticipate future trends.

SAP Predictive Analytics [EOL] was designed to integrate with existing SAP environments, allowing businesses to leverage their existing data infrastructure. It provided users with intuitive tools to automate data preparation and model management, simplifying complex analytical processes. Data scientists could efficiently build and deploy predictive models to address specific business questions. SAP emphasized ease of deployment and scalability, ensuring the platform met the needs of data-driven enterprises.

What are the key features?
  • Automated Model Creation: Streamlines the process of generating predictive models, reducing time and effort.
  • Data Preparation: Simplifies data cleaning and preparation, ensuring high-quality input for analysis.
  • Seamless Integration: Easily integrates with SAP environments, enhancing data accessibility.
What benefits should users consider in reviews?
  • Informed Decision-Making: Provides insights that help businesses make data-informed decisions.
  • Efficiency in Analysis: Reduces the time needed to develop and deploy predictive models.
  • Scalability: Supports expanding data needs as businesses grow.

In industries like manufacturing and retail, SAP Predictive Analytics [EOL] helped optimize supply chains and inventory management by forecasting demand trends. Financial sector users implemented it to enhance risk analysis and fraud detection models, providing valuable insights for mitigating potential risks.

SAP
 

Sample Customers

Reisebªro Idealtours GmbH, MedeAnalytics, Afni, Israel Electric Corporation, Nedbank Ltd., DigitalGlobe, Vodafone Hungary, Aegon Hungary, Bureau Veritas, Brammer Group, Florida Department of Juvenile Justice, InSites Consulting, Fortis Turkey
mBank
Buyer's Guide
Data Science Platforms
April 2026
Download Free Report
Find out what your peers are saying about Databricks, Dataiku, Amazon Web Services (AWS) and others in Data Science Platforms. Updated: April 2026.
DOWNLOAD NOW
886,932 professionals have used our research since 2012.
See our list of best Data Science Platforms vendors.

We monitor all Data Science Platforms 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.