IBM SPSS Modeler vs SAP Predictive Analytics comparison

IBM and SAP are both solutions in the Data Science Platforms category. IBM is ranked #17 with an average rating of 7.5, while SAP is ranked #27. IBM holds a 2.5% mindshare in Data Science Platforms, compared to SAP’s 0.5% 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

2,148 Views
1,418 Comparison Views

86% willing to recommend

SAP Predictive Analytics

Read 3 SAP Predictive Analytics reviews

303 Views
294 Comparison Views

100% willing to recommend

IBM SPSS Modeler

SAP Predictive Analytics

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

IBM SPSS Modeler and SAP Predictive Analytics are competitive analytics solutions known for their distinct advantages in the analytics software category. While IBM SPSS Modeler scores higher on pricing and support, SAP Predictive Analytics is favored due to its advanced features, considered worth its higher cost.

Features: IBM SPSS Modeler includes intuitive drag-and-drop functionality, comprehensive data preparation tools, and seamless model building. SAP Predictive Analytics offers sophisticated automation, scalability, and complex predictive modeling capabilities suitable for large enterprise environments.

Ease of Deployment and Customer Service: IBM SPSS Modeler allows simplified deployment with extensive integration options for quick installation and setup, complemented by responsive and expert customer service. SAP Predictive Analytics provides flexible deployment models and robust support, albeit with a potentially longer setup time due to the resources required.

Pricing and ROI: IBM SPSS Modeler presents a competitive setup cost, providing an attractive initial investment with solid ROI for cost-efficient businesses. SAP Predictive Analytics requires a higher initial expenditure but delivers significant ROI through its predictive capabilities and scalability, favored by enterprises seeking long-term value.

To learn more, read our detailed IBM SPSS Modeler vs. SAP Predictive Analytics Report (Updated: July 2025).

Buyer's Guide

IBM SPSS Modeler vs. SAP Predictive Analytics

July 2025

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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

17th

Average Rating

8.0

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

Data Mining (4th)

SAP Predictive Analytics

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 September 2025, in the Data Science Platforms category, the mindshare of IBM SPSS Modeler is 2.5%, up from 2.5% compared to the previous year. The mindshare of SAP Predictive Analytics is 0.5%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
IBM SPSS Modeler	2.5%
SAP Predictive Analytics	0.5%
Other	97.0%

Data Science Platforms

Featured Reviews

PeterHuo

Application Architect at Canada Border Services Agency

Good tool for extracting data from data warehouses, creating streams, and manipulating logic to extract final data

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. When streams become larger, performance bottlenecks may occur in the IBM SPSS Modeler server or the database. Sometimes the server crashes and needs to be restarted to release memory on both sides. I'm not sure exactly where the problem is caused, as I focus on stream design rather than server issues. The problem could be on the IBM SPSS Modeler server and database.

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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.

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Quotes from Members

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

Pros

"We are using it either for workforce deployment or to improve our operations."

"It's a very organized product. It's easy to use."

"I was familiar with using IBM SPSS Modeler separately in the private sector before that. It's a good tool for extracting data from data warehouses, creating streams, and manipulating logic to extract final data."

"It handles large data better than the previous system that we were using, which was basically Excel and Access. We serve upwards of 300,000 parts over a 150 regions and we need to crunch a lot of numbers."

"It's very easy to use. The drag and drop feature makes it very easy when you are building and testing the streams. That's very useful."

"So far, the stability has been rock solid."

"The quality is very good."

"It makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler."

More IBM SPSS Modeler pros

"I think the features of the actual ability to forecast and pull trends and correlations has been really good."

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

Cons

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

"I would not rate the technical support very well. The technicians have accents. When you do find someone, it is very hard to get somebody able to answer the technical questions."

"I would like see more programming languages added, like MATLAB. That would be better."

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

"The integration with sources and visualisation needs some improvement. The scalability needs improvement."

"I would like better integration into the Weather Company solution. I have raised a couple of concerns about this integration and having more time series capabilities."

"Dimension reduction should be classified separately."

"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."

Pricing and Cost Advice

"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."

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

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

"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."

"It is a huge increase to time savings."

"$5,000 annually."

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

"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

12%

Educational Organization

11%

Government

10%

University

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 do you like most about IBM SPSS Modeler?

Compared to other tools, the product works much easier to analyze data without coding.

See all answers

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

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Comparisons

IBM SPSS Statistics vs IBM SPSS Modeler

Compared 29% of the time

Microsoft Power BI vs IBM SPSS Modeler

Compared 21% of the time

KNIME Business Hub vs IBM SPSS Modeler

Compared 14% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 6% of the time

Alteryx vs IBM SPSS Modeler

Compared 6% of the time

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Microsoft Azure Machine Learning Studio vs SAP Predictive Analytics

Compared 52% of the time

KNIME Business Hub vs SAP Predictive Analytics

Compared 48% of the time

More SAP Predictive Analytics Competitors

Product Reports

Buyer's Guide

IBM SPSS Modeler

September 2025

Download IBM SPSS Modeler product report

Buyer's Guide

Data Science Platforms

August 2025

Download SAP Predictive Analytics 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

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https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947

IBM

SAP® Predictive Analytics software brings predictive insight to business users, analysts, data scientists, and developers in your company. Unlock the potential of Big Data from virtually any source with the power of predictive automation. By automating the building and management of sophisticated predictive models to deliver insight in real time, this software makes it easier to make better, more profitable decisions across the enterprise.

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

IBM SPSS Modeler vs. SAP Predictive Analytics

July 2025

Free Report: IBM SPSS Modeler vs. SAP Predictive Analytics

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