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Google Cloud AI Platform vs Microsoft Azure Machine Learning Studio comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jul 27, 2025

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

Google Cloud AI Platform
Ranking in AI Development Platforms
9th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
9
Ranking in other categories
No ranking in other categories
Microsoft Azure Machine Lea...
Ranking in AI Development Platforms
4th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
62
Ranking in other categories
Data Science Platforms (4th)
 

Mindshare comparison

As of September 2025, in the AI Development Platforms category, the mindshare of Google Cloud AI Platform is 3.6%, down from 6.3% compared to the previous year. The mindshare of Microsoft Azure Machine Learning Studio is 4.8%, down from 10.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Market Share Distribution
ProductMarket Share (%)
Microsoft Azure Machine Learning Studio4.8%
Google Cloud AI Platform3.6%
Other91.6%
AI Development Platforms
 

Featured Reviews

Vipul-Kumar - PeerSpot reviewer
An AI platform AI Platform to train your machine learning models at scale, to host your trained model in the cloud, and to use your model to make predictions about new data
I think it's the it it also has has evolved quite a bit over the last few years, and Google Cloud folks have been getting, more and more services. But I think from a improvement standpoint, so maybe they can look at adding more algorithms, so adding more AI algorithms to their suite.
Takayuki Umehara - PeerSpot reviewer
Streamlined workflows with drag and drop convenience but needs enhancements in AI
I use Machine Learning Studio for system reselling and integration Machine Learning Studio is easy to use, with a significant feature being the drag and drop interface that enhances workflow without any complaints. It provides a return on investment and cost savings, proving beneficial for…

Quotes from Members

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

Pros

"I have seen measurable benefits from Google Cloud AI Platform."
"A range of a a wide range of algorithms, EIM voice mails, which can be plugged in right away into your solution into into into our solution, and then have platform that provides know, to to come up with an operational solution really quick."
"The initial setup is very straightforward."
"On GCP, we are exposing our API services to our clients so that they send us their information. It can be single individual records or it can be a batch of their clients."
"The feedback left about these tools was really helpful and informative for us"
"Since the model could be trained in just a couple of hours and deploying it took only a few minutes, the entire process took less than an hour."
"I think the user interface is quite handy, and it is easy to use as compared to the other cloud platforms."
"Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture."
"The product is well organized. The thing is how we will get the models to work within our code. We have some suggestions there, but we want to gain more experience and be ready to answer that because we are currently working on this and don't have all the answers yet. The tool is well organized. What I am very happy about is the ease of deploying new resources. You can easily create your pipeline within minutes."
"Visualisation, and the possibility of sharing functions are key features."
"The solution's most beneficial feature is its integration with Azure."
"Split dataset, variety of algorithms, visualizing the data, and drag and drop capability are the features I appreciate most."
"In terms of what I found most valuable in Microsoft Azure Machine Learning Studio, I especially love the designer because you can just drag and drop items there and apply the logic that's already available with the designer. I love that I can use the libraries in Microsoft Azure Machine Learning Studio, so I don't have to search for the algorithms and all the relevant libraries because I can see them directly on the designer just by dragging and dropping. Though there's a bit of work during data cleansing, that's normal and can't be avoided. At least it's easy to find the relevant algorithm, apply that algorithm to the data, then get the desired output through Microsoft Azure Machine Learning Studio. I also like the API feature of the solution which is readily available for me to expose the output to any consuming application, so that takes out a lot of headache. Otherwise, I have to have a developer who knows the API, and I have to have an API app, so all that is completely taken care of by the Microsoft Azure Machine Learning Studio designer. With the solution, I can concentrate on how to improve the data quality to get quality recommendations, so this lets me concentrate on my job rather than focusing on the regular development of APIs or the pipelines, in particular, the data pipelines pulling the data from other sources. All the data is taken care of and you can also concentrate on other required auxiliary activities rather than just concentrating on machine learning."
"The graphical nature of the output makes it very easy to create PowerPoint reports as well."
"It's a great option if you are fairly new and don't want to write too much code."
"Machine Learning Studio is easy to use, with a significant feature being the drag and drop interface that enhances workflow without any complaints."
 

Cons

"It could be more clear, and sometimes there are errors that I don't quite understand."
"One thing that I found is that Azure ML does not directly provide you with features on Google Cloud AI Platform, whereas Vertex provides some features of the platform."
"Improvements in text extraction accuracy and pricing adjustments would be helpful."
"The technical support from Google is not very fast. I think it is about a five out of ten even though they have courses online where I can learn a lot, if I really need support, I have to wait a very long time."
"At first, there were only the user-managed rules to identify the best attributes of the individual. Then, we came up with a truth set and developed different machine learning models with the help of that truth set, so now it's completely machine learning."
"The model management on Google Cloud AI Platform could be better."
"The solution can be improved by simplifying the process to make your own models."
"The initial setup was straightforward for me but could be difficult for others."
"The interface is a bit overloaded."
"The speed of deployment should be faster, as should testing."
"There's room for improvement in terms of binding the integration with Azure DevOps."
"I rate the support from Microsoft as five out of ten. It could be improved."
"The data cleaning functionality is something that could be better and needs to be improved."
"I cannot comment on specific improvements yet as we are still exploring and need more time to identify the areas that require enhancements."
"Using the solution requires some specific learning which can take some time."
"While ML Studio does give you the ability to run a lot of transformations, it struggles when the transformations are a bit more complex, when your entire process is transformation-heavy."
 

Pricing and Cost Advice

"The solution has an attractive starting program, which costs only 300 USD for a duration of three months. During this period, one can accomplish a lot of work on the solution."
"The licenses are cheap."
"For every thousand uses, it is about four and a half euros."
"The price of the solution is competitive."
"The pricing is on the expensive side."
"The platform's price is low."
"When we got our first models and were ready for the user acceptance testing, our licensing fees were between €2,500 ($2,750 USD) and €3,000 ($3,300 USD) monthly."
"Last year, we paid 60,000 for Microsoft Azure Machine Learning Studio in our department."
"The pricing for Microsoft products can be complex due to changes and being cloud-based, so it's not straightforward. I've been familiar with it for years, but sometimes details about product licenses and distribution can be unclear. For Microsoft Azure Machine Learning Studio specifically, I would rate the price a six out of ten."
"I would rate the pricing an eight out of ten, with ten being very expensive. Not very expensive, not very cheap."
"There is a license required for this solution."
"ML Studio's pricing becomes a numbers game."
"The product's pricing is reasonable."
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Top Industries

By visitors reading reviews
Computer Software Company
15%
Financial Services Firm
10%
Manufacturing Company
9%
University
8%
Financial Services Firm
12%
Computer Software Company
9%
Manufacturing Company
9%
University
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise2
Large Enterprise2
By reviewers
Company SizeCount
Small Business23
Midsize Enterprise6
Large Enterprise30
 

Questions from the Community

What do you like most about Google Cloud AI Platform?
A range of a a wide range of algorithms, EIM voice mails, which can be plugged in right away into your solution into into into our solution, and then have platform that provides know, to to come up...
What is your experience regarding pricing and costs for Google Cloud AI Platform?
For the most part, the pricing is perfect sinceit grows with the use of my app. In some cases, they could be more specific about the pricing, especially for some AI features.
What is your primary use case for Google Cloud AI Platform?
I use Google Cloud AI Platform due to Firebase and the many APIs that are available with it.
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 do you like most about Microsoft Azure Machine Learning Studio?
The learning curve is very low. Operationalizing the model is also very easy within the Azure ecosystem.
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.
 

Also Known As

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

Overview

 

Sample Customers

Carousell
Walgreens Boots Alliance, Schneider Electric, BP
Find out what your peers are saying about Google Cloud AI Platform vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: July 2025.
867,370 professionals have used our research since 2012.