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 7.9, while IBM is ranked #13 with an average rating of 7.0. Amazon Web Services (AWS) holds a 7.6% mindshare in Data Science Platforms, compared to IBM’s 2.3% 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

7,315 Views
5,868 Comparison Views

91% willing to recommend

IBM SPSS Modeler

Read 39 IBM SPSS Modeler reviews

2,062 Views
1,679 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: January 2025).

Buyer's Guide

Amazon SageMaker vs. IBM SPSS Modeler

January 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 (4th)

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 February 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 7.6%, down from 9.9% compared to the previous year. The mindshare of IBM SPSS Modeler is 2.3%, down from 2.8% 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.

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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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Quotes from Members

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

Pros

"The most valuable features include the ML operations that allow for designing, deploying, testing, and evaluating models."

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

"The technical support from AWS is excellent."

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

"Allows you to create API endpoints."

"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 most valuable features are the ability to store artifacts and gather reports and measures from experiments."

"I recommend SageMaker for ML projects if you need to build models from scratch."

More Amazon SageMaker pros

"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."

"We use analytics with the visual modeling capability to leverage productivity improvements."

"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 works fine. I have not had any stability issues; it is always up."

"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."

"I think the code modeling features are the most valuable and without the need to write a code back with many different possibilities to choose from. And the second one is linked to the activity of the data preparation."

"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."

"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."

More IBM SPSS Modeler pros

Cons

"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."

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

"One area where Amazon SageMaker could improve is its pricing. The high costs can drive companies to explore other cloud options. Additionally, while generally good, the updates sometimes come with bugs, and the documentation could be much better. More examples and clearer guidance would be helpful."

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

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

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

"The solution requires a lot of data to train the model."

"For any cloud provider, the cost has to be substantially reduced, especially in the case of Amazon SageMaker, which is extremely expensive for huge workloads."

More Amazon SageMaker cons

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

"The time series should be improved."

"Regarding visual modeling, it is not the biggest strength of the product, although from what I hear in the latest release it's going to be a lot stronger. That, to me, has always been the biggest flaw in using this. It's very difficult to get good visualization."

"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."

"I think mapping for geographic data would also be a really great thing to be able to use."

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

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

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

More IBM SPSS Modeler cons

Pricing and Cost Advice

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

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

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

"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."

"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 product is expensive."

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

"Amazon SageMaker is a very expensive product."

More Amazon SageMaker pricing and cost advice

"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."

"It is an expensive product."

"$5,000 annually."

"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."

"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."

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

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

More IBM SPSS Modeler pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Educational Organization

15%

Computer Software Company

11%

Manufacturing Company

Educational Organization

13%

Financial Services Firm

12%

Computer Software Company

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?

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

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Compared 15% of the time

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Product Reports

Buyer's Guide

Amazon SageMaker

February 2025

Download Amazon SageMaker product report

Buyer's Guide

IBM SPSS Modeler

January 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

January 2025

Free Report: Amazon SageMaker vs. IBM SPSS Modeler

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