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 6.2% mindshare in Data Science Platforms, compared to IBM’s 2.5% 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 37 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: June 2025).

Buyer's Guide

Amazon SageMaker vs. IBM SPSS Modeler

June 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

7.1

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 July 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 6.2%, down from 9.3% compared to the previous year. The mindshare of IBM SPSS Modeler is 2.5%, 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

"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."

"The feature I found most valuable is the data catalog, as it assists with the lineage of data through the preparation pipeline."

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

"The technical support from AWS is excellent."

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

"The various integration options available in Amazon SageMaker, such as Firehose for connecting to data pipelines, are simple to use."

"The intuitive interface and streamlined user experience make it easy to navigate and set up various tools like Visual Studio Code or Jupyter Notebook."

"The support is very good with well-trained engineers whose training curriculum is rigorous."

More Amazon SageMaker pros

"A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly."

"You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after."

"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."

"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."

"New algorithms are added into every version of Modeler, e.g., SMOTE, random forest, etc. The Derive node is used for the syntax code to derive the data."

"It is pretty scalable."

"It gives you a GUI interface, which is a lot more user-friendly and easier to use compared to writing R scripts or Python."

"Some basic form of feature engineering for classification models. This really quickens the model development process."

More IBM SPSS Modeler pros

Cons

"The training modules could be enhanced. We had to take in-person training to fully understand SageMaker, and while the trainers were great, I think more comprehensive online modules would be helpful."

"In general, improvements are needed on the performance side of the product's graphical user interface-related area since it consumes a lot of time for a user."

"One area for improvement is the pricing, which can be quite high."

"The pricing of the solution is an issue...In SageMaker, monitoring could be improved by supporting more data types other than JSON and CSV."

"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."

"Amazon might need to emphasize its capabilities in generative models more effectively."

"AI is a new area and AWS needs to have an internship training program available."

"Lacking in some machine learning pipelines."

More Amazon SageMaker cons

"The product does not have a search function for tags."

"I understand that it takes some time to incorporate some of the new algorithms that have come out in the last few months, in the literature. For example, there is an algorithm based on how ants search for food. And there are some algorithms that have now been developed to complement rules. So that's one of the things that we need to have incorporated into it."

"Unstructured data is not appropriate for SPSS Modeler."

"When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing."

"The forecasting could be a bit easier."

"It's not as user friendly as it could be."

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

"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."

More IBM SPSS Modeler cons

Pricing and Cost Advice

"The solution is relatively cheaper."

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

"The cost offers a pay-as-you-go pricing model. It depends on the instance that you do."

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

"The tool's pricing is reasonable."

"Amazon SageMaker is a very expensive product."

"The pricing is complicated as it is based on what kind of machines you are using, the type of storage, and the kind of computation."

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

More Amazon SageMaker pricing and cost advice

"$5,000 annually."

"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."

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

"It is an expensive product."

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

"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."

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

"When you are close to end of quarter, IBM and its partners can get you 60% to 70% discounts, so literally wait for the last day of the quarter for the best prices. You may feel like you are getting robbed if you can't receive a good discount."

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

12%

Manufacturing Company

Educational Organization

Financial Services Firm

12%

Educational Organization

11%

Government

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...

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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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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

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

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

June 2025

Free Report: Amazon SageMaker vs. IBM SPSS Modeler

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