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

IBM SPSS Modeler

SAP Predictive Analytics [EOL]

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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.

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April 2026

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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

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

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
Product	Mindshare (%)
IBM SPSS Modeler	3.2%
SAP Predictive Analytics	1.4%
Other	95.4%

Data Science Platforms

Featured Reviews

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.

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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

"The benefits are that this product makes us a more efficient sales staff, reducing the inefficiencies in the buying patterns of our customers by calling them when we know they're ready to order, instead of waiting for them to call us."

"We have been able to do some predictive modeling with it"

"We had an IBM Guardium service contract where we used one of their resources to help us develop our prototype. It was a good experience, but they were helpful and responsive."

"It helped me in that I didn't need to write them by hand, and I could get a result in one or two minutes. That helped me a lot."

"It is a pretty stable solution, the end-users and other people with hands-on experience are very happy with this tool, it has not let us down in the past, and we have not really experienced any downtime."

"It continues to be a very flexible platform, so that it handles R and Python and other types of technology."

"We have a local representative who specializes in SPSS. He will help us do the PoC."

"It continues to be a very flexible platform, so that it handles R and Python and other types of technology. It seems to be growing with additional open-source movement out there on different platforms."

More IBM SPSS Modeler pros

"We always purchase SAP support because it is very good."

"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."

"I have found that the solution is very stable."

"The most valuable features are the analytics and reporting."

Cons

"It would be beneficial if the tool would include more well-known machine learning algorithms."

"The time series should be improved."

"It is very good, but slow. The slowness may be because we have not finalized all the background information in SPSS."

"Initial setup of the software was complex, because of our own problems within the government."

"Time Series or forecasting needs to be easier. It is a very important feature, and it should be made easier and more automated to use. For instance, for logistic regression, binary or multinomial is used automatically based on the type of the target variable. I wish they can make Time Series easier to use in a similar way."

"Easier coding language that is more flexible with other platforms."

"C&DS will not meet our scalability needs."

"Dimension reduction is very important, especially if you are working with millions of recordings and thousands of variables."

More IBM SPSS Modeler cons

"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."

"This solution works for acquired data but not live, real-time data."

Pricing and Cost Advice

"I am using the free version of IBM SPSS Modeler, it is the educational edition version."

"It is a huge increase to time savings."

"$5,000 annually."

"It got us a good amount of money with quick and efficient modeling."

"This tool, being an IBM product, is pretty expensive."

"Its price is okay for a company, but for personal use, it is considered somewhat expensive."

"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 users use the server with ten licenses, it runs faster. But if forty users use the same appliance, everything slows down. People then think it's not easy to do things and prefer using remote tools like Python to extract data from the database. It's not about being expensive or cheap, but about people's knowledge and experience in how to do the work."

"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."

More IBM SPSS Modeler pricing and cost advice

"The pricing is reasonable"

"A free trial version is available for testing out this solution."

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Top Industries

By visitors reading reviews

Financial Services Firm

11%

Government

10%

University

Outsourcing Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	4
Large Enterprise	32

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...

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What needs improvement with IBM SPSS Modeler?

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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...

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Compared 35% of the time

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Compared 5% of the time

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Compared 4% of the time

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Compared 4% of the time

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Compared 7% of the time

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Compared 7% of the time

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Compared 7% of the time

Altair RapidMiner vs SAP Predictive Analytics [EOL]

Compared 6% of the time

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Product Reports

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IBM SPSS Modeler

April 2026

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Buyer's Guide

Data Science Platforms

April 2026

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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

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