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Caffe vs Microsoft Azure Machine Learning Studio vs TensorFlow 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:
 

Mindshare comparison

As of March 2026, in the AI Development Platforms category, the mindshare of Caffe is 1.1%, up from 0.2% compared to the previous year. The mindshare of Microsoft Azure Machine Learning Studio is 3.5%, down from 7.6% compared to the previous year. The mindshare of TensorFlow is 5.3%, up from 3.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Mindshare Distribution
ProductMindshare (%)
Microsoft Azure Machine Learning Studio3.5%
TensorFlow5.3%
Caffe1.1%
Other90.1%
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.
TJ
Owner at Go knowledge
Has good stability, but the process of creating models could be more user-friendly
The platform integrates well with other tools, especially Python, which we use to create models. These models can be deployed on mobile devices, which perfectly suits our requirements. It supports our AI-driven initiatives very well by producing AI models, which is its primary function. I recommend it for those seeking specialized scripting. However, it's important to consider other options as well. It is better suited for specialists in the field and is less user-friendly than general tools like Excel. I rate it overall at six out of ten. While it is a powerful tool, other software options are slightly simpler for training models.

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."
"Their web interface is good."
"Anyone who isn't a programmer his whole life can adopt it. All he needs is statistics and data analysis skills."
"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."
"The graphical nature of the output makes it very easy to create PowerPoint reports as well."
"The solution is really scalable."
"The most valuable feature is data normalization."
"The drag-and-drop interface is good."
"The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout."
"It provides us with 35 features like patch normalization layers, and it is easy to implement using the Kras library when the Kaspersky flow is running behind it."
"TensorFlow provides Insights into both data and machine learning strategies."
"TensorFlow improves my organization because our clients get a lot of investment from their investors and we are progressively improving the products. Every six months we release new features."
"TensorFlow is an efficient product for building neural networks."
"It is also totally Open-Source and free. Open-source applications are not good usually. but TensorFlow actually changed my view about it and I thought, "Look, Oh my God. This is an open-source application and it's as good as it could be." I learned that TensorFlow, by sharing their own knowledge and their own platform with other developers, it improved the lives of many people around the globe."
"Optimization is very good in TensorFlow. There are many opportunities to do hyper-parameter training."
"Edge computing has some limited resources but TensorFlow has been improving in its features. It is a great tool for developers."
"It is open-source, and it is being worked on all the time. You don't have to pay all the big bucks like Azure and Databricks. You can just use your local machine with the open-source TensorFlow and create pretty good models."
 

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."
"The data cleaning functionality is something that could be better and needs to be improved."
"The pricing policy should be improved. I find the pricing to be not a good story in this case, as it is not affordable for everyone."
"The AutoML feature is very basic and they should improve it by using a more robust algorithm."
"They should have a desktop version to work on the platform."
"I personally would prefer if data could be tunneled to my model through a SAP ERP system, and have features of Excel, such as Pivot Tables, integrated."
"The data preparation capabilities need to be improved."
"Microsoft Azure Machine Learning Studio could improve by adding pixel or image analysis. This is a priority for me."
"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice."
"The process of creating models could be more user-friendly."
"There are a lot of problems, such as integrating our custom code. In my experience model tuning has been a bit difficult to edit and tune the graph model for best performance. We have to go into the model but we do not have a model viewer for quick access."
"It would be nice to have more pre-trained models that we can utilize within layers. I utilize a Mac, and I am unable to utilize AMD GPUs. That's something that I would definitely be like to be able to access within TensorFlow since most of it is with CUDA ML. This only matters for local machines because, in Azure, you can just access any GPU you want from the cloud. It doesn't really matter, but the clients that I work with don't have cloud accounts, or they don't want to utilize that or spend the money. They all see it as too expensive and want to know what they can do on their local machines."
"It doesn't allow for fast the proto-typing. So usually when we do proto-typing we will start with PyTorch and then once we have a good model that we trust, we convert it into TensorFlow. So definitely, TensorFlow is not very flexible."
"In terms of improvement, we always look for ways they can optimize the model, accelerate the speed and the accuracy, and how can we optimize with our different techniques. There are various techniques available in TensorFlow. Maintaining accuracy is an area they should work on."
"Enhancements could include increasing use cases and improving the accuracy of previously built models in TensorFlow. For instance, when we run certain models, the computing power of laptops becomes high."
"I would love to have a user interface like a programming interface. You need to have a set of menus where you can put things together in a graphical interface. The complete automation of the integration of the modules would also be interesting. It’s more like plumbing as opposed to a fully automated environment."
"It would be cool if TensorFlow could make it easier for companies like us to program for running it across different hyperscalers."
 

Pricing and Cost Advice

Information not available
"There isn’t any such expensive costs and only a standard license is required."
"The licensing cost is very cheap. It's less than $50 a month."
"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."
"The product is not that expensive."
"There is a lack of certainty with the solution's pricing."
"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."
"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 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."
"I think for learners to deploy a project, you can actually use TensorFlow for free. It's just amazing to have an open-source platform like TensorFlow to deploy your own project. Here in Russia no one really cares about licenses, as it is totally open source and free. My clients in the United States were also pleased to learn when they enquired, that licensing is free."
"I did not require a license for this solution. It a free open-source solution."
"I am using the open-source version of TensorFlow and it is free."
"I rate TensorFlow's pricing a five out of ten."
"The solution is free."
"It is open-source software. You don't have to pay all the big bucks like Azure and Databricks."
"We are using the free version."
"TensorFlow is free."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
11%
Manufacturing Company
8%
Computer Software Company
8%
Performing Arts
7%
Manufacturing Company
15%
Comms Service Provider
10%
University
9%
Financial Services Firm
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business23
Midsize Enterprise6
Large Enterprise30
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise3
Large Enterprise3
 

Questions from the Community

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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 ...
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...
What is your experience regarding pricing and costs for TensorFlow?
I am not familiar with the pricing setup cost and licensing.
What needs improvement with TensorFlow?
Providing more control by allowing users to build custom functions would make TensorFlow a better option. It currentl...
What is your primary use case for TensorFlow?
I've used TensorFlow for image classification tasks, object detection tasks, and OCR.
 

Also Known As

No data available
Azure Machine Learning, MS Azure Machine Learning Studio
No data available
 

Overview

 

Sample Customers

Information Not Available
Walgreens Boots Alliance, Schneider Electric, BP
Airbnb, NVIDIA, Twitter, Google, Dropbox, Intel, SAP, eBay, Uber, Coca-Cola, Qualcomm
Find out what your peers are saying about Google, Microsoft, Hugging Face and others in AI Development Platforms. Updated: March 2026.
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