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Hugging Face vs Microsoft Azure Machine Learning Studio 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

Hugging Face
Ranking in AI Development Platforms
4th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
12
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 Hugging Face is 13.5%, up from 7.6% 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

SwaminathanSubramanian - PeerSpot reviewer
Versatility empowers AI concept development despite the multi-GPU challenge
Regarding scalability, I'm finding the multi-GPU aspect of it challenging. Training the model is another hurdle, although I'm only getting into that aspect currently. Organizations are apprehensive about investing in multi-GPU setups. Additionally, data cleanup is a challenge that needs to be resolved, as data must be mature and pristine.
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

"There are numerous libraries available, and the documentation is rich and step-by-step, helping us understand which model to use in particular conditions."
"What I find the most valuable about Hugging Face is that I can check all the models on it and see which ones have the best performance without using another platform."
"I like that Hugging Face is versatile in the way it has been developed."
"The most valuable features are the inference APIs as it takes me a long time to run inferences on my local machine."
"My preferred aspects are natural language processing and question-answering."
"Hugging Face provides open-source models, making it the best open-source and reliable solution."
"I appreciate the versatility and the fact that it has generalized many models."
"I would rate this product nine out of ten."
"Their support is 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."
"Their web interface is good."
"Overall, I rate Microsoft Azure Machine Learning Studio a seven out of ten."
"Auto email and studio are great features."
"Machine Learning Studio is easy to use."
"​It has helped in reducing the time involved for coding using R and/or Python."
"Regarding the technical support for the solution, I find the documentation provided comprehensive and helpful."
 

Cons

"Initially, I faced issues with the solution's configuration."
"Implementing a cloud system to showcase historical data would be beneficial."
"The solution must provide an efficient LLM."
"I've worked on three projects using Hugging Face, and only once did we encounter a problem with the code. We had to use another open-source embedding from OpenAI to resolve it. Our team has three members: me, my colleague, and a team leader. We looked at the problem and resolved it."
"The area that needs improvement would be the organization of the materials. It could be clearer and more systematic. It would be good if the layout was clear and we could search the models easily."
"Regarding scalability, I'm finding the multi-GPU aspect of it challenging."
"Hugging Face could improve by implementing a search engine or chat bot feature similar to ChatGPT."
"Access to the models and datasets could be improved."
"The product must improve its documentation."
"The solution's initial setup process is complicated."
"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."
"They should have a desktop version to work on the platform."
"The data cleaning functionality is something that could be better and needs to be improved."
"I would like to see modules to handle Deep Learning frameworks."
"The pricing policy should be improved."
"In terms of improvement, I'd like to have more ability to construct and understand the detailed impact of the variables on the model. Their algorithms are very powerful and they explain overall the net contribution of each of the variables to the solution. In terms of being able to say to people "If you did this, you'll get this much more improvement" it wasn't great."
 

Pricing and Cost Advice

"The tool is open-source. The cost depends on what task you're doing. If you're using a large language model with around 12 million parameters, it will cost more. On average, Hugging Face is open source so you can download models to your local machine for free. For deployment, you can use any cloud service."
"I recall seeing a fee of nine dollars, and there's also an enterprise option priced at twenty dollars per month."
"The solution is open source."
"So, it's requires expensive machines to open services or open LLM models."
"We do not have to pay for the product."
"Hugging Face is an open-source solution."
"The solution operates on a pay-per-use model."
"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."
"Last year, we paid 60,000 for Microsoft Azure Machine Learning Studio in our department."
"On a scale from one to ten, with ten being overpriced, I would rate the price of this solution at six."
"I used the free student license for a few months to operate the solution, but I'll have to pay for it if I want to do more now."
"I rate the product price as a nine on a scale of one to ten, where ten means it is very expensive."
"From a developer's perspective, I find the price of this solution high."
"ML Studio's pricing becomes a numbers game."
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Top Industries

By visitors reading reviews
Computer Software Company
11%
Financial Services Firm
11%
University
10%
Manufacturing Company
10%
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 Hugging Face?
My preferred aspects are natural language processing and question-answering.
What needs improvement with Hugging Face?
Access to the models and datasets could be improved. Many interesting ones are restricted. It would be great if they provided access for students or non-professionals who just want to test things.
What is your primary use case for Hugging Face?
This is a simple personal project, non-commercial. As a student, that's all I do.
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

Information Not Available
Walgreens Boots Alliance, Schneider Electric, BP
Find out what your peers are saying about Hugging Face vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: March 2025.
844,944 professionals have used our research since 2012.