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28 Ratings
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Likelihood to Recommend
Amazon SageMaker
SageMaker is great for serving Jupyter notebooks, particularly if you already use other AWS products, such as S3. SageMaker's model retraining function is useful if you write a few Lambda functions to invoke jobs. Its model serving function is useful if your team has limited resources and is willing to submit to SageMaker's opinions.
Data Scientist
Wonder (AskWonder.com)Research, 11-50 employees
IBM SPSS Modeler
Modeler is well suited for Retail, Credit Scoring, Telcos, Government. And less suited when it comes to transactional environments.
Gerente de Ventas Sector Gobierno
INFÓRMESEGovernment Relations, 11-50 employees
Pros
- SageMaker is useful as a managed Jupyter notebook server. Using the notebook instances' IAM roles to grant access to private S3 buckets and other AWS resources is great. Using SageMaker's lifecycle scripts and AWS Secrets Manager to inject connection strings and other secrets is great.
- SageMaker is good at serving models. The interface it provides is often clunky, but a managed, auto-scaling model server is powerful.
- SageMaker is opinionated about versioning machine learning models and useful if you agree with its opinions.
Data Scientist
Wonder (AskWonder.com)Research, 11-50 employees
- GUI is really well accomplished and friendly, almost everyone with little investment in training can take advantage of the tool.
- Escalability, you can grow your investment in licensing according to your actual needs, from an annual authorized user, to perpetual concurrent and Big Data and Machine Learning capabilities.
- Open Sorce Ready: take leverage of all your developments made in R or Python and deployment all over the organization even with the user who isn´t used to code.
Gerente de Ventas Sector Gobierno
INFÓRMESEGovernment Relations, 11-50 employees
Cons
- SageMaker does not allow you to schedule training jobs.
- SageMaker does not provide a mechanism for easily tracking metrics logged during training.
- We often fit feature extraction and model pipelines. We can inject the model artifacts into AWS-provided containers, but we cannot inject the feature extractors. We could provide our own container to SageMaker instead, but this is tantamount to serving the model ourselves.
Data Scientist
Wonder (AskWonder.com)Research, 11-50 employees
- Too much foreign programming software
Statistician
ManitobaInsurance, 501-1000 employees
Likelihood to Renew
No score
No answers yet
No answers on this topic
IBM SPSS Modeler10.0
Based on 1 answer
because it is an excellent software
Statistician
ManitobaInsurance, 501-1000 employees
Usability
No score
No answers yet
No answers on this topic
IBM SPSS Modeler10.0
Based on 1 answer
Easy to use
Statistician
ManitobaInsurance, 501-1000 employees
Support
No score
No answers yet
No answers on this topic
IBM SPSS Modeler9.0
Based on 1 answer
It's been a great deal
Statistician
ManitobaInsurance, 501-1000 employees
Implementation
No score
No answers yet
No answers on this topic
IBM SPSS Modeler8.0
Based on 1 answer
Everything seems to went on according to plan
Statistician
ManitobaInsurance, 501-1000 employees
Alternatives Considered
We have not invested in another machine learning software at this time and so far this has proved very successful with our machine learning teams. As mentioned, I am training these individuals simply on the fundamentals of the software and using it/customizing it for their needs. It has been very easy to do this and has gotten great reviews across the organization so far.

Verified User
Employee in Human Resources
Real Estate Company, 1001-5000 employeesWhen it comes to investigation and descriptive we have found SPSS Statistics to be the tool of choice, but when it comes to projects with large and several datasets SPSS Modeler has been picked from our customers.
Gerente de Ventas Sector Gobierno
INFÓRMESEGovernment Relations, 11-50 employees
Return on Investment
- We have been able to deliver data products more rapidly because we spend less time building data pipelines and model servers.
- We can prototype more rapidly because it is easy to configure notebooks to access AWS resources.
- For our use-cases, serving models is less expensive with SageMaker than bespoke servers.
Data Scientist
Wonder (AskWonder.com)Research, 11-50 employees
- Efficient result
- Validity of result
- Improved customer service
Statistician
ManitobaInsurance, 501-1000 employees
Screenshots
Pricing Details
Amazon SageMaker
General
Free Trial
—Free/Freemium Version
—Premium Consulting/Integration Services
—Entry-level set up fee?
No
Amazon SageMaker Editions & Modules
Amazon SageMaker
—
Additional Pricing Details
—IBM SPSS Modeler
General
Free Trial
Yes
Free/Freemium Version
—Premium Consulting/Integration Services
Yes
Entry-level set up fee?
Optional
IBM SPSS Modeler Editions & Modules
IBM SPSS Modeler
Edition
IBM SPSS Modeler Personal
$4,6701
IBM SPSS Modeler Professional
$7,0001
IBM SPSS Modeler Premium
$11,6001
IBM SPSS Modeler Gold
contact IBM1
1. per year