Amazon SageMaker vs IBM SPSS Modeler comparison

Amazon Web Services (AWS) and IBM are both solutions in the Data Science Platforms category. Amazon Web Services (AWS) is ranked #3 with an average rating of 8.0, while IBM is ranked #17 with an average rating of 7.0. Amazon Web Services (AWS) holds a 6.1% mindshare in Data Science Platforms, compared to IBM’s 2.6% mindshare. Additionally, 91% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 86% of IBM users who would recommend it.

Amazon SageMaker

Read 38 Amazon SageMaker reviews

7,896 Views
4,738 Comparison Views

91% willing to recommend

IBM SPSS Modeler

Read 39 IBM SPSS Modeler reviews

2,280 Views
1,528 Comparison Views

86% willing to recommend

Amazon SageMaker

IBM SPSS Modeler

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

IBM SPSS Modeler and Amazon SageMaker are competitive in the data analytics and machine learning platforms category. SPSS Modeler may have the upper hand in providing comprehensive analytics, whereas SageMaker offers broader utility in machine learning environments, especially with cloud integration.

Features: IBM SPSS Modeler includes advanced statistical analysis tools, intuitive data mining, and data manipulation features. It provides a point-and-click interface that simplifies complex analytical tasks. Amazon SageMaker offers a robust machine learning suite, integration with AWS infrastructure, and capabilities for building, training, and deploying models at scale.

Room for Improvement: IBM SPSS Modeler could improve its cloud deployment capabilities and expand integration options with modern data platforms. It might also benefit from enhancing its visualization features. Amazon SageMaker could improve by providing more extensive pre-built models, simplifying onboarding for complex tasks, and enhancing offline capabilities for hybrid environments.

Ease of Deployment and Customer Service: Amazon SageMaker offers seamless deployment within the AWS ecosystem, which is advantageous for large-scale projects. It provides comprehensive support with extensive documentation and active channels. IBM SPSS Modeler supports multiple platforms but may face challenges in cloud environments. Customer service is reliable but lacks the depth found in SageMaker's support structure.

Pricing and ROI: IBM SPSS Modeler usually requires higher upfront costs due to its specialized analytics capabilities, leading to solid ROI for dedicated analytical tasks. In contrast, Amazon SageMaker presents a flexible pricing model that aligns with usage patterns, potentially offering better cost-effectiveness for projects with varying demands. SageMaker's cloud synergy can contribute to greater overall value.

To learn more, read our detailed Amazon SageMaker vs. IBM SPSS Modeler Report (Updated: July 2025).

Buyer's Guide

Amazon SageMaker vs. IBM SPSS Modeler

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

Amazon SageMaker

Ranking in Data Science Platforms

3rd

Average Rating

7.8

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

AI Development Platforms (5th)

IBM SPSS Modeler

Ranking in Data Science Platforms

17th

Average Rating

8.0

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Data Mining (4th)

Mindshare comparison

As of August 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 6.1%, down from 8.8% compared to the previous year. The mindshare of IBM SPSS Modeler is 2.6%, up from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Saurabh Jaiswal

Python AWS & AI Expert at a tech consulting company

Create innovative assistants with seamless data integration for large-scale projects

The various integration options available in Amazon SageMaker ( /products/amazon-sagemaker-reviews ), such as Firehose for connecting to data pipelines, are simple to use. Tools like AWS Glue ( /products/aws-glue-reviews ) integrate well for data transformations. The Databricks ( /products/databricks-reviews ) integration aids data scientists and engineers. SageMaker is fully managed, offers high availability, flexibility with TensorFlow ( /products/tensorflow-reviews ), PyTorch ( /products/pytorch-reviews ), and MXNet ( /products/mxnet-reviews ), and comes with pre-trained algorithms for forecasting, anomaly detection, and more.

Read full review

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.

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

"SageMaker is a comprehensive platform where I can perform all machine learning activities."

"The solution is easy to scale...The documentation and online community support have been sufficient for us so far."

"I have contacted the solution's technical support, and they were really good. I rate the technical support a ten out of ten."

"Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in Amazon SageMaker."

"The tool has made client management easier where patients need to upload their health records and we can use the tool to understand details on treatment date, amount, etc."

"We've had no problems with SageMaker's stability."

"The most valuable feature of Amazon SageMaker is its integration. For example, AWS Lambda. Additionally, we can write Python code."

"We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for these models, making accessing them convenient as needed."

More Amazon SageMaker pros

"The visual modeling capability is one of its attractive features."

"It is just a lot faster. So you do not have to write a bunch of code, you can throw that stuff on there pretty quickly and do prototyping quickly."

"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."

"Automated modelling, classification, or clustering are very useful."

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

"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."

"Very good data aggregation."

"We have full control of the data handling process."

More IBM SPSS Modeler pros

Cons

"I would recommend having more walkthrough videos and articles beyond AWS Skill Builder."

"I had to create custom templates for labeling multi-data sets, such as text and images, which was time-consuming."

"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."

"SageMaker would be improved with the addition of reporting services."

"In my opinion, one improvement for Amazon SageMaker would be to offer serverless GPUs. Currently, we incur costs on an hourly basis. It would be beneficial if the tool could provide pay-as-you-go pricing based on endpoints."

"The product must provide better documentation."

"There is room for improvement in the collaboration with serverless architecture, particularly integration with AWS Lambda."

"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."

More Amazon SageMaker cons

"I can say the solution is outdated."

"The time series should be improved."

"When I used it in the office, back in the day, we did have some stability issues. Sometimes it just randomly crashed and we couldn't get good feedback. But when I use it for my own stuff now I don't have any problems."

"Neural networks are quite simple, and now neural networks are evolving to these architecture related to deep learning, etc. They didn't incorporate this in IBM SPSS Modeler."

"Dimension reduction should be classified separately."

"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."

"It would be helpful if SPSS supported open-source features, for example, embedding R or Python scripts in SPSS Modeler."

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

More IBM SPSS Modeler cons

Pricing and Cost Advice

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a six out of ten."

"I would rate the solution's price a ten out of ten since it is very high."

"The support costs are 10% of the Amazon fees and it comes by default."

"On average, customers pay about $300,000 USD per month."

"The product is expensive."

"In terms of pricing, I'd also rate it ten out of ten because it's been beneficial compared to other solutions."

"SageMaker is worth the money for our use case."

"The pricing could be better, especially for querying. The per-query model feels expensive."

More Amazon SageMaker pricing and cost advice

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

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

"It is a huge increase to time savings."

"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."

"If you are in a university and the license is free then you can use the tool without any charges, which is good."

"It is an expensive product."

More IBM SPSS Modeler pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Computer Software Company

11%

Manufacturing Company

University

Financial Services Firm

11%

Educational Organization

11%

Government

10%

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

See all answers

What do you like most about Amazon SageMaker?

We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for t...

See all answers

What is your experience regarding pricing and costs for Amazon SageMaker?

The pricing is high, around an eight. However, SageMaker offers free trials for the first two months, allowing users to determine which features they need. It is considered value for money given it...

See all answers

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?

See all answers

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Compared 25% of the time

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Compared 24% of the time

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Compared 14% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 7% of the time

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Product Reports

Buyer's Guide

Amazon SageMaker

July 2025

Download Amazon SageMaker product report

Buyer's Guide

IBM SPSS Modeler

July 2025

Download IBM SPSS Modeler product report

Also Known As

AWS SageMaker, SageMaker

SPSS Modeler

Overview

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.

Amazon Web Services (AWS)

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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IBM

Sample Customers

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit

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

Buyer's Guide

Amazon SageMaker vs. IBM SPSS Modeler

July 2025

Free Report: Amazon SageMaker vs. IBM SPSS Modeler

Find out what your peers are saying about Amazon SageMaker vs. IBM SPSS Modeler and other solutions. Updated: July 2025.

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