What users are saying about
21 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener noreferrer'>trScore algorithm: Learn more.</a>Score 8.1 out of 100
Based on 21 reviews and ratings
20 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener noreferrer'>trScore algorithm: Learn more.</a>Score 6.8 out of 100
Based on 20 reviews and ratings
Likelihood to Recommend
Amazon SageMaker
Amazon SageMaker is a great tool for developing machine learning models that take more effort than just point-and-click type of analyses. The software works well with the other tools in the Amazon ecosystem, so if you use Amazon Web Services or are thinking about it, SageMaker would be a great addition. SageMaker is great for consumer insights, predictive analytics, and looking for gems of insight in the massive amounts of data we create. SageMaker is less suitable for analysts who do generally "small" data analyses, and "small" data analyses in today's world can be billions of records.
Owner, previous CEO
Econometric StudiosFinancial Services, 11-50 employees
Azure Machine Learning Studio
For [a] data scientist require[d] to build a machine learning model, so he/she didn't worry about infrastructure to maintain it.
All kind of feature[s] such as train, build, deploy and monitor the machine learning model available in a single suite.
If someone has [their] own environment for ML studio, so there [it would] not [be] useful for them.

Verified User
Professional in Information Technology
Information Technology & Services Company, 10,001+ employeesPros
Amazon SageMaker
- Provides enough freedom for experienced data scientists and also for those who just need things done without going much deeper into building models.
- Customization and easy to alter and change.
- If you already are an Amazon user, you do not need to transition over to another software.

Verified User
Employee in Human Resources
Real Estate Company, 1001-5000 employeesAzure Machine Learning Studio
- User friendliness: This is by far the most user friendly tool I've seen in analytics. You don't need to know how to code at all! Just create a few blocks, connect a few lines and you are capable of running a boosted decision tree with a very high R squared!
- Speed: Azure ML is a cloud based tool, so processing is not made with your computer, making the reliability and speed top notch!
- Cost: If you don't know how to code, this is by far the cheapest machine learning tool out there. I believe it costs less than $15/month. If you know how to code, then R is free.
- Connectivity: It is super easy to embed R or Python codes on Azure ML. So if you want to do more advanced stuff, or use a model that is not yet available on Azure ML, you can simply paste the code on R or Python there!
- Microsoft environment: Many many companies rely on the Microsoft suite. And Azure ML connects perfectly with Excel, CSV and Access files.
MBA Candidate | Class of 2018
Brigham Young University Marriott School of BusinessConsumer Electronics, 201-500 employees
Cons
Amazon SageMaker
- It's very good for the hardcore programmer, but a little bit complex for a data scientist or new hire who does not have a strong programming background.
- Most of the popular library and ML frameworks are there, but we still have to depend on them for new releases.

Verified User
Employee in Research & Development
Computer Software Company, 501-1000 employeesAzure Machine Learning Studio
- It would be great to have text tips that could ease new users to the platform, especially if an error shows up
- Scenario-based documentation
- Pre-processing of modules that had been previously run. Sometimes they need to be re-run for no apparent reason

Verified User
Professional in Information Technology
Education Management Company, 1001-5000 employeesUsability
Amazon SageMaker
No score
No answers yet
No answers on this topic
Azure Machine Learning Studio
Azure Machine Learning Studio 7.0
Based on 2 answers
Easy and fastest way to develop, test, deploy and monitor the machine learning model.
- Easy to load the data set
-Drag and drop the process of the Machine learning life cycle.

Verified User
Professional in Information Technology
Information Technology & Services Company, 10,001+ employeesSupport Rating
Amazon SageMaker
No score
No answers yet
No answers on this topic
Azure Machine Learning Studio
Azure Machine Learning Studio 6.1
Based on 2 answers
Support is nonexistent. It's very frustrating to try and find someone to actually talk to. The robot chatbots are just not well trained.

Verified User
Professional in Information Technology
Education Management Company, 1001-5000 employeesImplementation Rating
Amazon SageMaker
No score
No answers yet
No answers on this topic
Azure Machine Learning Studio
Azure Machine Learning Studio 8.0
Based on 1 answer
Not sure

Verified User
Professional in Information Technology
Information Technology & Services Company, 10,001+ employeesAlternatives Considered
Amazon SageMaker
Amazon SageMaker took the heavy lifting out of building and creating models. It allowed for our organization to use our current system for integration and essentially added on a feature to help all levels of Data scientists and IT professionals in our department and company as a whole. The training was simple as well.

Verified User
Professional in Legal
Legal Services Company, 51-200 employeesAzure Machine Learning Studio
It is easier to learn, it has a very cost effective license for use, it has native build and created for Azure cloud services, and that makes it perfect when compared against the alternatives. As a Microsoft tool, it has been built to contain many visual features and improved usability even for non-specialist users.

Verified User
Team Lead in Information Technology
Machinery Company, 10,001+ employeesReturn on Investment
Amazon SageMaker
- 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
Azure Machine Learning Studio
- Productivity: Instead of coding and recoding, Azure ML helped my organization to get to meaningful results faster;
- Cost: Azure ML can save hundreds (or even thousands) of dollars for an organization, since the license costs around $15/month per seat.
- Focus on insights and not on statistics: Since running a model is so easy, analysts can focus more on recommendations and insights, rather than statistical details
MBA Candidate | Class of 2018
Brigham Young University Marriott School of BusinessConsumer Electronics, 201-500 employees
Pricing Details
Amazon SageMaker
General
Free Trial
—Free/Freemium Version
—Premium Consulting/Integration Services
—Entry-level set up fee?
No
Amazon SageMaker Editions & Modules
—
Additional Pricing Details
—Azure Machine Learning Studio
General
Free Trial
—Free/Freemium Version
—Premium Consulting/Integration Services
—Entry-level set up fee?
No
Azure Machine Learning Studio Editions & Modules
Edition
Studio Pricing - Free | $0.001 |
---|---|
Studio Pricing - Standard | $9.992 |
Production Web API - Dev/Test | $0.003 |
Production Web API - Standard S1 | $100.133 |
Production Web API - Standard S2 | $1000.063 |
Production Web API - Standard S3 | $9999.983 |
- per month
- per ML studio workspace/per month
- per month