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Google Cloud AI Platform vs Microsoft Azure Machine Learning Studio comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 12, 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
8th
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
3rd
Average Rating
7.6
Reviews Sentiment
7.0
Number of Reviews
61
Ranking in other categories
Data Science Platforms (4th)
 

Mindshare comparison

As of April 2025, in the AI Development Platforms category, the mindshare of Google Cloud AI Platform is 4.3%, down from 6.6% compared to the previous year. The mindshare of Microsoft Azure Machine Learning Studio is 7.3%, down from 13.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
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

"Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture."
"The platform's Google Vision API is particularly valuable."
"The solution is able to read 90% of the documents correctly with a 10% error rate."
"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"
"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."
"I think the user interface is quite handy, and it is easy to use as compared to the other cloud platforms."
"I have seen measurable benefits from Google Cloud AI Platform."
"Machine Learning Studio is easy to use, with a significant feature being the drag and drop interface that enhances workflow without any complaints."
"The integration with Azure services enhances workflow and meets my expectations."
"The solution facilitates our production."
"The solution is very easy to use, so far as our data scientists are concerned."
"When you import the dataset you can see the data distribution easily with graphics and statistical measures."
"Anyone who isn't a programmer his whole life can adopt it. All he needs is statistics and data analysis skills."
"Regarding the technical support for the solution, I find the documentation provided comprehensive and helpful."
"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."
 

Cons

"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."
"The solution can be improved by simplifying the process to make your own models."
"It could be more clear, and sometimes there are errors that I don't quite understand."
"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."
"Customizations are very difficult, and they take time."
"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."
"Improvements in text extraction accuracy and pricing adjustments would be helpful."
"The model management on Google Cloud AI Platform could be better."
"The high price of the product is an area of concern where improvements are required."
"The pricing policy should be improved. I find the pricing to be not a good story in this case, as it is not affordable for everyone."
"It is not easy. It is a complex solution. It takes some time to get exposed to all the concepts. We're trying to have a CI/CD pipeline to deploy a machine learning model using negative actions. It was not easy. The components that we're using might have something to do with this."
"I cannot comment on specific improvements yet as we are still exploring and need more time to identify the areas that require enhancements."
"Microsoft Azure Machine Learning Studio could improve by adding pixel or image analysis. This is a priority for me."
"The product must improve its documentation."
"Easier customization and configuration would be beneficial."
"One problem I experience is that switching between multiple accounts can be difficult. I don't think there are any major issues. Mostly, the biggest challenge is to identify business solutions to this. The tool should keep on updating new algorithms and not stay static."
 

Pricing and Cost Advice

"The pricing is on the expensive side."
"For every thousand uses, it is about four and a half euros."
"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."
"The price of the solution is competitive."
"On a scale from one to ten, with ten being overpriced, I would rate the price of this solution at six."
"From a developer's perspective, I find the price of this solution high."
"Last year, we paid 60,000 for Microsoft Azure Machine Learning Studio in our department."
"My team didn't deal with the licensing for Microsoft Azure Machine Learning Studio, so I'm unable to comment on pricing, but the money that was spent on the tool was worth it."
"I rate the solution's pricing a four on a scale of one to ten, where one is cheap, and ten is expensive."
"There isn’t any such expensive costs and only a standard license is required."
"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 rate the product price as a nine on a scale of one to ten, where ten means it is very expensive."
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Top Industries

By visitors reading reviews
Computer Software Company
16%
Financial Services Firm
11%
Manufacturing Company
9%
University
8%
Financial Services Firm
13%
Computer Software Company
11%
Manufacturing Company
10%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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?
Pricing is considered to be top-segment and should be improved. I rate the pricing as three or four on a scale of one to ten in terms of affordability.
 

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: March 2025.
844,944 professionals have used our research since 2012.