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Microsoft Azure Machine Learning Studio vs OpenVINO comparison

 

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
5th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
62
Ranking in other categories
Data Science Platforms (5th)
OpenVINO
Ranking in AI Development Platforms
13th
Average Rating
8.2
Reviews Sentiment
6.3
Number of Reviews
7
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2026, in the AI Development Platforms category, the mindshare of Microsoft Azure Machine Learning Studio is 3.5%, down from 8.0% compared to the previous year. The mindshare of OpenVINO is 1.9%, up from 1.6% 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 Studio3.5%
OpenVINO1.9%
Other94.6%
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.
Mahender Reddy Pokala - PeerSpot reviewer
AI Developer at University of Chicago
Improved model deployment on edge devices, but compatibility and scalability present challenges
I found OpenVINO's ability to convert custom models into its format particularly beneficial, as businesses sometimes require unique models specific to their use cases. Utilizing OpenVINO allowed me to run these custom models on devices directly, which I found quite impressive. Additionally, the Model Zoo offered by OpenVINO added value to the product.

Quotes from Members

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

Pros

"Azure Machine Learning Studio provides a platform to integrate with large language models."
"The product supports open-source tools."
"The AutoML is helpful when you're starting to explore the problem that you're trying to solve."
"Azure's AutoML feature is probably better than the competition."
"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."
"I like that it's totally easy to use. They have an AutoML solution, and their machine learning model is highly accurate. They also have a feature that can explain the machine learning model. This makes it easy for me to understand that model."
"Scalability, in terms of running experiments concurrently is good. At max, I was able to run three different experiments concurrently."
"Machine Learning Studio is easy to use, with a significant feature being the drag and drop interface that enhances workflow without any complaints."
"The runtime of OpenVINO is highly valuable for running different computer vision models."
"The benefit from using OpenVINO is that NVIDIA is dominating the market of GPUs and they set the price, so if I am able to run an LLM doing inference in commodity hardware, I am saving costs."
"Intel's support team is very good."
"The features for model comparison, the feature for model testing, evaluation, and deployment are very nice. It can work almost with all the models."
"The inferencing and processing capabilities are quite beneficial for our requirements."
"One positive aspect about OpenVINO is that it supports more frameworks than the Google Coral TPU."
"The initial setup is quite simple."
 

Cons

"The price could be improved."
"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice."
"The regulatory requirements of the product need improvement."
"The initial setup of Microsoft Azure Machine Learning Studio was rigorous for someone new like me, but mastering it made things simpler."
"The solution cannot connect to private block storage."
"Overall, the icons in the solution could be improved to provide better guidance to users. Additionally, the setup process for the solution could be made easier."
"They should have a desktop version to work on the platform."
"In the Machine Learning Studio, particularly the Designer part, which is essentially Azure's demo designer, there is room for improvement. Many customers and users tend to switch to Microsoft Azure Multi-Joiners, which is a more basic version, but they do so internally. One area that could use enhancement is the process of connecting components. Currently, every time you want to connect a component, such as linking it to your storage or an instance like EC2, you have to input your username and password repeatedly. This can be quite cumbersome. Google, for instance, has made it more user-friendly by allowing easy access for connecting services within a workspace. In a workspace, you can set up various resources like storage, a database cluster, machine learning studio, and more. When connecting these services, there's no need to enter your username and password each time, making it a more efficient process. Another aspect to consider is the role of the designer, and they were to integrate a large language model to handle various tasks, it could significantly enhance the overall scalability and usability of the platform."
"I think that it's not properly designed for scalability. It's designed for other purposes, specifically to be able to use Intel hardware and run inference using generative models or deep learning models in Intel hardware."
"I couldn't get it to run on my Raspberry Pi 4 because the software packages to download were no longer available."
"The model optimization is a little bit slow — it could be improved."
"Scalability is a challenge with OpenVINO, particularly when I try to connect multiple streams of input or run multiple edge devices consecutively."
"It has some disadvantages because when you're working with very complex models, neural networks if OpenVINO cannot convert them automatically and you have to do a custom layer and later add it to the model. It is difficult."
"At this point, the product could probably just use a greater integration with more machine learning model tools."
"It would be great if OpenVINO could convert new models into its format more quickly."
 

Pricing and Cost Advice

"ML Studio's pricing becomes a numbers game."
"On a scale from one to ten, with ten being overpriced, I would rate the price of this solution at six."
"The solution cost is high."
"The licensing cost is very cheap. It's less than $50 a month."
"I would rate the pricing an eight out of ten, with ten being very expensive. Not very expensive, not very cheap."
"The solution operates on a pay-per-use model."
"There is a license required for this solution."
"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."
"We didn't have to pay for any licensing with Intel OpenVINO. Everything is available on their site and easily downloadable for free."
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Top Industries

By visitors reading reviews
Financial Services Firm
10%
Manufacturing Company
9%
Computer Software Company
8%
Performing Arts
7%
Manufacturing Company
31%
Financial Services Firm
9%
Comms Service Provider
9%
Educational Organization
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business23
Midsize Enterprise6
Large Enterprise30
No data available
 

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 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.
What needs improvement with OpenVINO?
I have heard good things about OpenVINO. It doesn't consume much current for external GPU usage. However, it has some downsides because I couldn't get it to run on my Raspberry Pi 4. While not spec...
What is your primary use case for OpenVINO?
I wanted to use OpenVINO for my Raspberry Pi to analyze my sleep with a night vision camera and to improve GPU performance on my Raspberry Pi. I would have used OpenVINO's Model Optimizer feature t...
 

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. OpenVINO and other solutions. Updated: February 2026.
882,886 professionals have used our research since 2012.