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Caffe vs Microsoft Azure Machine Learning Studio comparison

 

Comparison Buyer's Guide

Executive Summary

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

Caffe
Ranking in AI Development Platforms
27th
Average Rating
7.0
Reviews Sentiment
6.0
Number of Reviews
1
Ranking in other categories
No ranking in other categories
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)
 

Mindshare comparison

As of January 2026, in the AI Development Platforms category, the mindshare of Caffe is 0.9%, up from 0.2% compared to the previous year. The mindshare of Microsoft Azure Machine Learning Studio is 3.4%, down from 8.4% 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%
Caffe0.9%
Other95.7%
AI Development Platforms
 

Featured Reviews

RL
Machine/Deep Learning Engineer at UpWork Freelancer
Speeds up the development process but needs to evolve more to stay relevant
In the future, they should expand text processing, for a recommendation system, or to support some other models as well — that would be great. The concept of Caffe is a little bit complex because it was developed and based in C++. They need to make it easier for a new developer, data scientist, or a new machine or deep learning engineer to understand it. You can't work with metrics and vectors as Python does. Python is a vector-oriented language, but Caffe is not. When you deal with memory in C++, you have to allocate the data you will use in memory. You have to manage everything in C++. Conversely, in Python, you don't need to do that since everything is abstract and done by Python itself. It depends on every use case or your requirement goals. Some clients will require you to use Caffe because maybe their projects are old and they want to continue with Caffe. Others are comfortable with their current situation or they are afraid of migrating to another library. From my point of view, they need to make it easier for a new developer to use it. They should incorporate Python API to make it richer, overall.
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.

Quotes from Members

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

Pros

"Caffe has helped our company become up-to-date in the market and has helped us speed up the development process of our projects."
"The solution's most beneficial feature is its integration with Azure."
"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 learning curve is very low. Operationalizing the model is also very easy within the Azure ecosystem."
"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 a great option if you are fairly new and don't want to write too much code."
"The solution is very easy to use, so far as our data scientists are concerned."
"I find Microsoft Azure Machine Learning Studio advantageous because it allows integration with Titan Scratch and offers an easy-to-use drag-and-drop menu for developing machine learning models."
"It is very easy to test different kinds of machine-learning algorithms with different parameters. You choose the algorithm, drag and drop to the workspace, and plug the dataset into this component."
 

Cons

"The concept of Caffe is a little bit complex because it was developed and based in C++. They need to make it easier for a new developer, data scientist, or a new machine or deep learning engineer to understand it."
"One area where Azure Machine Learning Studio could improve is its user interface structure."
"The high price of the product is an area of concern where improvements are required."
"In the future, I would like to see more AI consultation like image and video classification, and improvement in the presentation of data."
"We can create a label job, but we still have to use the Azure Machine Learning REST APIs, which are not yet supported in the Python SDK version 2."
"Microsoft Azure Machine Learning Studio could improve by adding pixel or image analysis. This is a priority for me."
"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."
"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."
"Performance is very poor."
 

Pricing and Cost Advice

Information not available
"The licensing cost is very cheap. It's less than $50 a month."
"I rate the product price as a nine on a scale of one to ten, where ten means it is very expensive."
"I rate the solution's pricing a four on a scale of one to ten, where one is cheap, and ten is expensive."
"The solution cost is high."
"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."
"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."
"There is a license required for this solution."
"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."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
11%
Manufacturing Company
9%
Computer Software Company
9%
Performing Arts
6%
 

Company Size

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

Questions from the Community

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Earn 20 points
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.
 

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 Microsoft, Hugging Face, Google and others in AI Development Platforms. Updated: January 2026.
881,114 professionals have used our research since 2012.