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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

"​It has helped in reducing the time involved for coding using R and/or Python."
"Split dataset, variety of algorithms, visualizing the data, and drag and drop capability are the features I appreciate most."
"The platform as a service provides user-friendly instruments, making the experience easy."
"Visualisation, and the possibility of sharing functions are key features."
"Auto email and studio are great features."
"When you import the dataset you can see the data distribution easily with graphics and statistical measures."
"Azure Machine Learning Studio's most valuable features are the package from Azure AutoML. It is quite powerful compared to the building of ML in Databricks or other AutoMLs from other companies, such as Google and Amazon."
"I like being able to compare results across different training runs. The hyperparameter tuning function is a valuable feature because it provides the ability to run multiple experiments at the same time and compare results."
"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 runtime of OpenVINO is highly valuable for running different computer vision models."
"The initial setup is quite simple."
"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."
 

Cons

"It would be nice if the product offered more accessibility in general."
"One area where Azure Machine Learning Studio could improve is its user interface structure."
"Microsoft Azure Machine Learning Studio could improve in providing more efficient and cost-effective access to its tools for companies like mine."
"Using the solution requires some specific learning which can take some time."
"Machine Learning Studio is more dependent on legacy Machine Learning algorithms. It would be beneficial for them to incorporate more services required for LLMs or LLM evaluation."
"The data cleaning functionality is something that could be better and needs to be improved."
"The solution must increase the amount of data sources that can be integrated."
"The regulatory requirements of the product need improvement."
"The model optimization is a little bit slow — it could be improved."
"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."
"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."
"Scalability is a challenge with OpenVINO, particularly when I try to connect multiple streams of input or run multiple edge devices consecutively."
"I couldn't get it to run on my Raspberry Pi 4 because the software packages to download were no longer available."
 

Pricing and Cost Advice

"The product is not that expensive."
"It is less expensive than one of its competitors."
"There isn’t any such expensive costs and only a standard license is required."
"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 rate the product price as a nine on a scale of one to ten, where ten means it is very expensive."
"The solution cost is high."
"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."
"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 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
11%
Manufacturing Company
9%
Computer Software Company
8%
Performing Arts
6%
Manufacturing Company
32%
Financial Services Firm
8%
Comms Service Provider
8%
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: December 2025.
881,360 professionals have used our research since 2012.