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Microsoft Azure Machine Learning Studio vs PyTorch comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Dec 4, 2024

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

Microsoft Azure Machine Lea...
Ranking in AI Development Platforms
6th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
62
Ranking in other categories
Data Science Platforms (9th)
PyTorch
Ranking in AI Development Platforms
12th
Average Rating
8.6
Reviews Sentiment
6.7
Number of Reviews
13
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of September 2026, in the AI Development Platforms category, the mindshare of Microsoft Azure Machine Learning Studio is 3.1%, down from 4.8% compared to the previous year. The mindshare of PyTorch is 2.1%, down from 3.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Mindshare Distribution
ProductMindshare (%)
Microsoft Azure Machine Learning Studio3.1%
PyTorch2.1%
Other94.8%
AI Development Platforms
 

Featured Reviews

reviewer2722962 - PeerSpot reviewer
Data Scientist
Platform accelerates model development, enhances collaboration, and offers efficient deployment
The best features Microsoft Azure Machine Learning Studio offers include deep integration with Python notebooks and Azure Data Lake, which allows me to import external data, and through the pipeline, I can build my models, performing what is called data injection for my model building, making that deep integration quite interesting to use. Microsoft Azure Machine Learning Studio is a powerful platform for those already in the Azure ecosystem because it allows for scalability and provides a good environment for reproducibility, as well as collaboration tools, all designed and packaged in one place, which makes it outstanding. Microsoft Azure Machine Learning Studio has positively impacted my organization by reducing our project delivery times and increasing the pace at which we work, allowing us to focus on other more important tasks. Using Microsoft Azure Machine Learning Studio has reduced our model development time from approximately four hours to about two hours.
Rohan Sharma - PeerSpot reviewer
AI/ML Co-Lead at Developer Student Clubs - GGV
Enabled creation of innovative projects through developer-friendly features
The aspect I like most about PyTorch is that it is really developer-friendly. Developers can constantly create new things, and everyone around the world can use it for free because it's an open-source product. What I personally like is that PyTorch has enabled users to use Apple's M1 chip natively for GPU users. Unlike other libraries using CUDA, PyTorch utilizes Metal Performance Shaders (MPS) to enable GPU usage on M1 chips.

Quotes from Members

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

Pros

"The solution is very easy to use, so far as our data scientists are concerned."
"The notebook feature allows you to write inquiries and create dashboards. These dashboards can integrate with multiple databases, such as Excel, HANA, or SQL Server."
"It's a great option if you are fairly new and don't want to write too much code."
"The solution is really scalable."
"Their web interface is good."
"Microsoft Azure Machine Learning Studio offers a hands-on experience with lots of flexibility."
"The drag-and-drop interface of Azure Machine Learning Studio has greatly improved my workflow."
"The most valuable feature of Azure Machine Learning Studio for me is its convenience. I can quickly start using it without setting up the environment or buying a lot of devices."
"It's been pretty scalable in terms of using multiple GPUs."
"I like PyTorch's scalability."
"The tool is very user-friendly."
"yTorch is gaining credibility in the research space, it's becoming easier to find examples of papers that use PyTorch. This is an advantage for someone who uses PyTorch primarily."
"Its interface is the most valuable, and the ability to have an interface to train machine learning models and construct them with the high-level interface, without excess busting and reconstructing the same technical elements, is very useful."
"We use PyTorch libraries, which are working well. It's very easy."
"The framework of the solution is valuable."
"I like that PyTorch actually follows the pythonic way, and I feel that it's quite easy. It's easy to find compared to others who require us to type a long paragraph of code."
 

Cons

"The solution must increase the amount of data sources that can be integrated."
"They should have a desktop version to work on the platform."
"Microsoft should also include more examples and tutorials for using this product.​"
"Enable creating ensemble models easier, adding more machine learning algorithms."
"Some of the terminologies, or the way that the questions are asked, could be stronger."
"The AutoML feature is very basic and they should improve it by using a more robust algorithm."
"The initial setup of Microsoft Azure Machine Learning Studio was rigorous for someone new like me, but mastering it made things simpler."
"I would like to see modules to handle Deep Learning frameworks."
"There is not enough documentation about some methods and parameters. It is sometimes difficult to find information."
"The product has certain shortcomings in the automation of machine learning."
"I've had issues with stability when I use a lot of data and try out different combinations of modeling techniques."
"The analyzing and latency of compiling could be improved to provide enhanced results."
"I would like a model to be available. I think Google recently released a new version of EfficientNet. It's a really good classifier, and a PyTorch implementation would be nice."
"On the production side of things, having more frameworks would be helpful."
"PyTorch could make certain things more obvious. Even though it does make things like defining loss functions and calculating gradients in backward propagation clear, these concepts may confuse beginners. We find that it's kind of problematic. Despite having methods called on loss functions during backward passes, the oral documentation for beginners is quite complex."
"I do not have any complaints."
 

Pricing and Cost Advice

"The licensing cost is very cheap. It's less than $50 a month."
"To use MLS is fairly cheap. Even the paid account is something like $20/month, unless you are provisioning large numbers of VMs for a Hadoop cluster. The main MS makes money with this solution is forcing the user to deploy their model on REST API, and being charged each time the API is accessed. There are several pricing tiers for the API. If you do not use the API, then value of MLS is to create rapid experiments ($20/month). The resulting model is not exportable to use, thus you’ll have to recreate the algorithms in either R or Python, which is what I did. MLS results gave me a direction to work with, the actual work is mostly done in R and Python outside of MLS."
"I am paying for it following a pay-as-you-go. So, the more I use it, the more it costs."
"There is a license required for this solution."
"In terms of pricing, for any cloud solution, you should know the tricks of the trade and how to use it, otherwise, you'll end up paying a lot of money irrespective of the cloud provider, so at least for Microsoft Azure Machine Learning Studio pricing versus AWS, I would rate it three out of five, with one being the most expensive, and five being the cheapest. It could be cheaper, but you also have to be careful when choosing the plans, for example, consider the architecture and a lot of other factors before choosing your plan, if you don't want to end up paying more. If your cloud provider has an optimizer that seems to be available in every provider, that would keep alerting you in terms of resources not being used as much, then that would help you with budgeting."
"We pay only the Azure costs for what we use, which involves some subscription costs. But essentially, you pay for what you use. There are no extra costs in addition to the standard licensing fees."
"On a scale from one to ten, with ten being overpriced, I would rate the price of this solution at six."
"I rate the solution's pricing a four on a scale of one to ten, where one is cheap, and ten is expensive."
"PyTorch is open-sourced."
"It is free."
"The solution is affordable."
"PyTorch is an open-source solution."
"It is free."
"PyTorch is open source."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Outsourcing Company
12%
Performing Arts
7%
Construction Company
7%
Manufacturing Company
13%
University
12%
Comms Service Provider
10%
Financial Services Firm
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business23
Midsize Enterprise6
Large Enterprise32
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise4
Large Enterprise6
 

Questions from the Community

Which do you prefer - Databricks or Azure Machine Learning Studio?
Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...
What is your experience regarding pricing and costs for Microsoft Azure Machine Learning Studio?
The pricing for Microsoft Azure Machine Learning Studio is reasonable since it's pay as you go, meaning it won't cost excessively unless specific resources are used.
What needs improvement with Microsoft Azure Machine Learning Studio?
The initial setup can be a bit challenging for someone new, as the learning curve can be steep, but once I master the platform, I find it quite manageable. I would love to see the integration of a ...
What is your experience regarding pricing and costs for PyTorch?
I haven't gone for a paid plan yet. I've just been using the free trial or open-source version.
What needs improvement with PyTorch?
There are a few areas for improvement. The biggest one for me is version and dependency management, as I have to ensure my Torch, TorchAudio, and CUDA versions are all aligned. If one is off, thing...
What is your primary use case for PyTorch?
I have been using PyTorch for the last three years, mostly through my thesis work and model deployment projects. I use PyTorch for pretty much everything in my deep learning work, specifically to b...
 

Also Known As

Azure Machine Learning, MS Azure Machine Learning Studio
No data available
 

Overview

 

Sample Customers

Walgreens Boots Alliance, Schneider Electric, BP
Information Not Available
Find out what your peers are saying about Microsoft Azure Machine Learning Studio vs. PyTorch and other solutions. Updated: September 2026.
913,806 professionals have used our research since 2012.