Try our new research platform with insights from 80,000+ expert users

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 January 2026, in the AI Development Platforms category, the mindshare of Microsoft Azure Machine Learning Studio is 3.4%, down from 8.4% compared to the previous year. The mindshare of OpenVINO is 1.9%, up from 1.7% 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 Studio3.4%
OpenVINO1.9%
Other94.7%
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

"The UI is very user-friendly and that AI is easy to use."
"The product's standout feature is a robust multi-file network with limited availability."
"The learning curve is very low. Operationalizing the model is also very easy within the Azure ecosystem."
"The solution is very fast and simple for a data science solution."
"Azure's AutoML feature is probably better than the competition."
"The visualizations are great. It makes it very easy to understand which model is working and why."
"The most valuable feature of Microsoft Azure Machine Learning Studio is the ease of use for starting projects. It's simple to connect and view the results. Additionally, the solution works well with other Microsoft solutions, such as Power Automate or SQL Server. It is easy to use and to connect for analytics."
"It's easy to deploy."
"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."
"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."
"The runtime of OpenVINO is highly valuable for running different computer vision models."
"The initial setup is quite simple."
"Intel's support team is very good."
"One positive aspect about OpenVINO is that it supports more frameworks than the Google Coral TPU."
 

Cons

"The interface is a bit overloaded."
"The solution cannot connect to private block storage."
"It would be great if the solution integrated Microsoft Copilot, its AI helper."
"Improvement in integration is crucial, and it'll be interesting to see how it develops, especially with SAP's move towards cloud-based solutions like SAP Rise and its collaboration with hyper scalers like AWS. Integrating SAP with hyperscaler machine learning solutions could simplify operations, although SAP's environment is complex. SAP has initiated deals with AWS for this purpose, but I'm not as familiar with Microsoft Azure Machine Learning Studio's involvement."
"As for the areas for improvement in Microsoft Azure Machine Learning Studio, I've provided feedback to Microsoft. My company is a Gold Partner of Microsoft, so I provided my feedback in another forum. Right now, it is the number of algorithms available in the designer that has to be improved, though I'm sure Microsoft does it regularly. When you take a use case approach, Microsoft has done that in a lot of places, but not on the Microsoft Azure Machine Learning Studio designer. When I say use case basis, I meant recommending a product or recommending similar products, so if Microsoft can list out use cases and give me a template, it will save me a lot of time and a lot of work because I don't have to scratch my head on which algorithm is better, and I can go with what's recommended by Microsoft. I'm sure that isn't a big task for the Microsoft team who must have seen thousands of use cases already, so out of that experience if the team can come up with a standard template, I'm sure it'll help a lot of organizations cut down on the development time, as well as going with the best industry-standard algorithms rather than experimenting with mine. What I'd like to see in the next version of Microsoft Azure Machine Learning Studio, apart from the use case template, is the improvement of the availability of libraries. Microsoft should also upgrade the Python versions because the old version of Python is still supported and it takes time for Microsoft to upgrade the support for Python. The pace of upgrading Python versions of Microsoft Azure Machine Learning Studio and making those libraries available should be sped up or increased."
"n the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces."
"Enable creating ensemble models easier, adding more machine learning algorithms."
"I think it should be made cheaper for certain people…It may appear costlier for those who don't consider time important."
"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."
"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."
"I couldn't get it to run on my Raspberry Pi 4 because the software packages to download were no longer available."
"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."
"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."
 

Pricing and Cost Advice

"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."
"The solution operates on a pay-per-use model."
"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 solution's pricing a four on a scale of one to ten, where one is cheap, and ten is expensive."
"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."
"It is less expensive than one of its competitors."
"ML Studio's pricing becomes a numbers game."
"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."
report
Use our free recommendation engine to learn which AI Development Platforms solutions are best for your needs.
880,511 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
11%
Manufacturing Company
9%
Computer Software Company
8%
Performing Arts
6%
Manufacturing Company
31%
Financial Services Firm
9%
Comms Service Provider
8%
Educational Organization
6%
 

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.
880,511 professionals have used our research since 2012.