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 #13 with an average rating of 6.8. Amazon Web Services (AWS) holds a 7.3% mindshare in Data Science Platforms, compared to IBM’s 2.4% 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 36 Amazon SageMaker reviews

6,112 Views
4,892 Comparison Views

91% willing to recommend

IBM SPSS Modeler

Read 39 IBM SPSS Modeler reviews

1,793 Views
1,459 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: March 2025).

Buyer's Guide

Amazon SageMaker vs. IBM SPSS Modeler

March 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

13th

Average Rating

8.0

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Data Mining (4th)

Mindshare comparison

As of April 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 7.3%, down from 9.8% compared to the previous year. The mindshare of IBM SPSS Modeler is 2.4%, down from 2.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Hemant Paralkar

Lead Consultant at Saama

Improves team collaboration with advanced feature sharing but needs a better user experience

Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker. This would empower citizen data scientists to utilize the tool more effectively since many data scientists do not have a core development background. Additionally, dealing with frequent UI updates can be challenging, especially for infrastructure architects like myself. It involves effort to migrate to new UIs, making the updates not seamless. User auditing requires enhancements as tracking operations performed by users can be difficult due to dynamic IP validation and role propagation.

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

"Allows you to create API endpoints."

"The technical support of the tool was good."

"The few projects we have done have been promising."

"I have seen a return on investment, probably a factor of four or five."

"The Autopilot feature is really good because it's helpful for people who don't have much experience with coding or data pipelines. When we suggest SageMaker to clients, they don't have to go through all the steps manually. They can leverage Autopilot to choose variables, run experiments, and monitor costs. The results are also pretty accurate."

"The most valuable feature of Amazon SageMaker for me is the model deployment service."

"The tool makes our ML model development a bit more efficient because everything is in one environment."

"Amazon SageMaker is highly valuable for managing ML workloads. It connects to AWS cloud resources, making it easy to deploy algorithms and collaborate using tools like GitLab. It offers a wide range of Python libraries and other necessary tools for modelling and algorithms."

More Amazon SageMaker pros

"It is a great product for running statistical analysis."

"It is very scalable for non-technical people."

"Very good data aggregation."

"Our go live process has been slightly enhanced compared to the previous programmatic process. There is now a faster time to production from the business end."

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

"Stability is good."

"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."

"It will scale up to anything we need."

More IBM SPSS Modeler pros

Cons

"The product must provide better documentation."

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

"The main challenge with Amazon SageMaker is the integrations."

"Having all documentation easily accessible on the front page of SageMaker would be a great improvement."

"Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker."

"The dashboard could be improved by including more features and providing more information about deployed models, their drift, performance, scaling, and customization options."

"Amazon SageMaker can make it simpler to manage the data flow from start to finish, such as by integrating data, usingthe machine, and deploying models. This process could be more user-friendly compared to other tools. I would also like to improve integration with Bedrock and the LLM connection for AWS."

"The main challenge with Amazon SageMaker is the integrations."

More Amazon SageMaker cons

"The platform that you can deploy it on needs improvement because I think it is Windows only. I do not think it can run off a Red Hat, like the server products. I am pretty sure it is Windows and AIX only."

"It is not integrated with Qlik, Tableau, and Power BI."

"Requires more development."

"Formula writing is not straightforward for an Excel user. Totally new set of functions, which takes time to learn and teach."

"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."

"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."

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

"The standard package (personal) is not supported for database connection."

More IBM SPSS Modeler cons

Pricing and Cost Advice

"You don't pay for Sagemaker. You only pay for the compute instances in your storage."

"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."

"The tool's pricing is reasonable."

"Databricks solution is less costly than Amazon SageMaker."

"The solution is relatively cheaper."

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

"The pricing is comparable."

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

More Amazon SageMaker pricing and cost advice

"It is an expensive product."

"It is a huge increase to time savings."

"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."

"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."

"This tool, being an IBM product, is pretty 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%

Educational Organization

13%

Computer Software Company

11%

Manufacturing Company

Financial Services Firm

13%

Educational Organization

12%

University

Computer Software Company

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?

Before deploying SageMaker, I reviewed the pricing, especially for notebook instances. The cost for small to medium instances is not very high.

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

Comparisons

Databricks vs Amazon SageMaker

Compared 17% of the time

Azure OpenAI vs Amazon SageMaker

Compared 12% of the time

Dataiku vs Amazon SageMaker

Compared 10% of the time

Google Vertex AI vs Amazon SageMaker

Compared 9% of the time

Domino Data Science Platform vs Amazon SageMaker

Compared 7% of the time

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Microsoft Power BI vs IBM SPSS Modeler

Compared 29% of the time

IBM SPSS Statistics vs IBM SPSS Modeler

Compared 20% of the time

KNIME vs IBM SPSS Modeler

Compared 17% of the time

Altair RapidMiner vs IBM SPSS Modeler

Compared 7% of the time

SAS Analytics vs IBM SPSS Modeler

Compared 2% of the time

More IBM SPSS Modeler Competitors

Product Reports

Buyer's Guide

Amazon SageMaker

March 2025

Download Amazon SageMaker product report

Buyer's Guide

IBM SPSS Modeler

March 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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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

March 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: March 2025.

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