Try our new research platform with insights from 80,000+ expert users

Amazon SageMaker vs IBM SPSS Statistics comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

Review summaries and opinions

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

ROI

Sentiment score
7.3
Amazon SageMaker offers significant ROI with cost reductions, time savings, and notable financial benefits, especially in fraud detection and targeted ads.
Sentiment score
8.7
IBM SPSS Statistics boosts efficiency and decision-making, providing user-friendly data analysis and a 50% estimated ROI.
The return on investment varies by use case and offers significant value in revenue increases and cost saving capabilities, especially in real time fraud detection and targeted advertisements.
 

Customer Service

Sentiment score
7.2
Amazon SageMaker customer service has mixed reviews, with satisfaction varying based on user experience, support promptness, and service tier.
Sentiment score
6.6
IBM SPSS Statistics support experiences vary; some report satisfaction, others cite delays, with reliance on forums and self-help.
The technical support from AWS is excellent.
The support is very good with well-trained engineers.
 

Scalability Issues

Sentiment score
7.6
Amazon SageMaker is highly scalable, handling diverse data needs effectively but may require deployment expertise for optimal efficiency.
Sentiment score
6.5
IBM SPSS Statistics excels with moderate data, but struggles with Big Data due to licensing and resource limitations.
The availability of GPU instances can be a challenge, requiring proper planning.
Amazon SageMaker is scalable and works well from an infrastructure perspective.
 

Stability Issues

Sentiment score
7.8
Amazon SageMaker is stable and reliable, with minor issues mainly due to user configuration errors, not infrastructure problems.
Sentiment score
7.7
IBM SPSS Statistics is stable and reliable with occasional minor bugs, requiring adequate RAM for optimal performance.
I rate the stability of Amazon SageMaker between seven and eight.
 

Room For Improvement

Amazon SageMaker needs UI simplification, better documentation, cost efficiency improvements, enhanced security, scalability, training resources, and performance optimization.
IBM SPSS users seek improvements in cost, visualization, documentation, training, user interface, automation, and integration for enhanced usability.
Having all documentation easily accessible on the front page of SageMaker would be a great improvement.
Integration of the latest machine learning models like the new Amazon LLM models could enhance its capabilities.
This would empower citizen data scientists to utilize the tool more effectively since many data scientists do not have a core development background.
I'm unsure if SPSS has a commercial offering for big servers, unlike KNIME, which does.
 

Setup Cost

Amazon SageMaker is costly, especially for notebook instances, with better visibility needed to optimize pay-as-you-go costs.
IBM SPSS Statistics is often seen as expensive, with complex licensing, but offers discounts for educational institutions and annual enterprise licenses.
For a single user, prices might be high yet could be cheaper for user-managed services compared to AWS-managed services.
The pricing can be up to eight or nine out of ten, making it more expensive than some cloud alternatives yet more economical than on-premises setups.
The cost for small to medium instances is not very high.
 

Valuable Features

Amazon SageMaker provides flexible AI/ML solutions with easy AWS integration, strong deployment features, and comprehensive tools for scalability.
IBM SPSS Statistics offers robust analysis, user-friendly interface, and customizable features for effective data exploration and reporting.
These features facilitate rapid development and deployment of AI applications.
SageMaker supports building, training, and deploying AI models from scratch, which is crucial for my ML project.
This allows monitoring and performance grading, as I instantly know when someone has a bad call.
I mainly used it for cross tabs, correlation, regression, chi-squared tests, and similar analyses often seen in published papers.
 

Categories and Ranking

Amazon SageMaker
Ranking in Data Science Platforms
3rd
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
36
Ranking in other categories
AI Development Platforms (4th)
IBM SPSS Statistics
Ranking in Data Science Platforms
9th
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
38
Ranking in other categories
Data Mining (3rd)
 

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 Statistics is 2.7%, 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 - PeerSpot reviewer
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.
Md Masudul Hassan - PeerSpot reviewer
Comprehensive data analysis capabilities with a user-friendly interface, providing an efficient and reliable platform for researchers and analysts
I believe that offering short-term SPSS licenses, perhaps when customer sourcing is available, could make it more affordable. These licenses shouldn't include features tailored for universities or large sales organizations. Instead, they could offer discounts or additional facilities for smaller entities to access the software. In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options. For example, offering basic features to the first hundred users can help them become familiar with the software and its capabilities. This approach encourages users to upgrade to higher tiers as they become more experienced and require additional functionality.
report
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
838,640 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
18%
Educational Organization
14%
Computer Software Company
11%
Manufacturing Company
9%
Financial Services Firm
17%
Computer Software Company
9%
University
8%
Manufacturing Company
8%
 

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...
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...
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.
What do you like most about IBM SPSS Statistics?
The software offers consistency across multiple research projects helping us with predictive analytics capabilities.
What is your experience regarding pricing and costs for IBM SPSS Statistics?
SPSS is horrendously expensiver. On a laptop Knime is free of charge (Windows, Mac, Linux)
What needs improvement with IBM SPSS Statistics?
Better guidance both in producing programs and interpreting their output.
 

Also Known As

AWS SageMaker, SageMaker
SPSS Statistics
 

Overview

 

Sample Customers

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit
LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA
Find out what your peers are saying about Amazon SageMaker vs. IBM SPSS Statistics and other solutions. Updated: January 2025.
838,640 professionals have used our research since 2012.