Machine Learning & Data Science · head to head
AWS SageMaker vs IBM SPSS
AWS SageMaker
Machine Learning & Data Science
Build, train, and deploy machine learning models at scale
- From
- Free
- Rated
- -
IBM SPSS
Machine Learning & Data Science
Statistical analysis software for data science
- From
- Free
- Rated
- -
The short version
- Each has a real cost: AWS SageMaker vendor lock-in to AWS ecosystem makes migration to other platforms difficult; IBM SPSS add-on packages are priced separately from the base subscription, and the promotional 45% discount on them excludes renewals
- They diverge on capability: AWS SageMaker covers Jupyter notebooks, IBM SPSS covers Statistical analysis.
Where they differ
Only the attributes on which AWS SageMaker and IBM SPSS actually diverge.
| Attribute | AWS SageMaker | IBM SPSS |
|---|---|---|
| Pricing model | Unknown | subscription |
| Platforms | Web | Linux, Mac, Windows |
| Founded | 2006 | 1911 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning & Data Science).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in AWS SageMaker
- Jupyter notebooks
- Built-in algorithms
- Automatic model tuning
- One-click deployment
- Model monitoring
- S3
- Lambda
- Step Functions
Only in IBM SPSS
- Statistical analysis
- Predictive modeling
- Data visualization
- Survey analysis
- Decision trees
- Python
- R
- Excel
What people use each for
The jobs each tool is most often brought in to do.
AWS SageMaker
- Machine learningnot IBM SPSS
- Data analysisnot IBM SPSS
- Model trainingnot IBM SPSS
- Predictive analyticsnot IBM SPSS
IBM SPSS
- Statistical testing and regression analysis for academic and market researchnot AWS SageMaker
- Predictive modelling and forecasting without writing codenot AWS SageMaker
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
AWS SageMaker
- Vendor lock-in to AWS ecosystem makes migration to other platforms difficult
- Opaque pricing can lead to unexpected expenses like forgotten EBS volume charges
- Does not include native job scheduling, requiring Lambda or EventBridge integration
IBM SPSS
- Add-on packages are priced separately from the base subscription, and the promotional 45% discount on them excludes renewals
- Subscription cost renews at the then current price at the end of the first year, so the advertised rate applies to the first term only
- Prices shown are described by IBM as indicative, vary by country and exclude applicable taxes and duties
- Extended access periods of 12 months or more are handled as tailored pricing rather than a published rate
- Advanced statistics, custom tables, decision trees and forecasting are separate add-ons rather than part of the base product
Pricing, plan by plan
AWS SageMaker
FreeNo published plan breakdown. See the AWS SageMaker review.
IBM SPSS
Free- TrialFree
- 14-day trial
- Full features
- Base$99/month
- Core statistics
- Data management
Which should you pick?
Choose AWS SageMaker if
- You need jupyter notebooks.
- You want to start without paying.
- You also want built-in algorithms.
Choose IBM SPSS if
- You need statistical analysis.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want predictive modeling.
Questions people ask
- Is AWS SageMaker or IBM SPSS better?
- Neither clearly leads. AWS SageMaker starts at Free and IBM SPSS at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, AWS SageMaker or IBM SPSS?
- AWS SageMaker starts at Free and IBM SPSS at Free.
- Does AWS SageMaker or IBM SPSS run on more platforms?
- AWS SageMaker runs on Web. IBM SPSS runs on Linux, Mac, Windows.
- Can I use AWS SageMaker for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is AWS SageMaker best used for?
- AWS SageMaker is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what IBM SPSS is typically brought in for.
- What can AWS SageMaker do that IBM SPSS cannot?
- AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. IBM SPSS covers Statistical analysis, Predictive modeling, Data visualization, Survey analysis.
Answered from the vendors’ own pages
AWS SageMaker: What is AWS SageMaker used for?
AWS SageMaker is a machine learning service for building, training, and deploying ML models at scale. It provides tools for data preparation, model training, inference endpoints, and performance optimization.
SourceAWS SageMaker: How is AWS SageMaker priced?
SageMaker uses pay-as-you-go pricing with no upfront costs or long-term commitments. Pricing starts at $0.04 per hour for basic notebook instances and scales based on instance type. ML Savings Plans offer up to 64% off with hourly spend commitments.
SourceAWS SageMaker: Does AWS SageMaker have a free tier?
Yes, the free tier includes 250 hours of notebook usage, 50 hours of training, and 125 hours of hosting on ml.t3.medium instances during the first two months.
SourceRelated pages
More on AWS SageMaker
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