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Cloudera Data Science Workbench vs Microsoft Azure Machine Learning Studio comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 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

Cloudera Data Science Workb...
Ranking in Data Science Platforms
23rd
Average Rating
7.0
Reviews Sentiment
6.9
Number of Reviews
2
Ranking in other categories
No ranking in other categories
Microsoft Azure Machine Lea...
Ranking in Data Science Platforms
4th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
62
Ranking in other categories
AI Development Platforms (4th)
 

Mindshare comparison

As of July 2025, in the Data Science Platforms category, the mindshare of Cloudera Data Science Workbench is 1.3%, down from 1.7% compared to the previous year. The mindshare of Microsoft Azure Machine Learning Studio is 5.1%, down from 7.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

Ismail Peer - PeerSpot reviewer
Useful for data science modeling but improvement is needed in MLOps and pricing
If you don't configure CDSW well, then it might be not useful for you. Deploying the tool can vary in complexity, but most of the time, it's relatively simple and straightforward. Triggering a job from data to production is easy, as the platform automates the deployment process. However, ensuring optimal resource allocation is essential for smooth operations.
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

"I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don't interfere with each other. The deployment of machine learning is fast and easy to manage. Its API calls are also fast."
"The Cloudera Data Science Workbench is customizable and easy to use."
"When you import the dataset you can see the data distribution easily with graphics and statistical measures."
"The UI is very user-friendly and that AI is easy to use."
"Split dataset, variety of algorithms, visualizing the data, and drag and drop capability are the features I appreciate most."
"The most valuable feature is its compatibility with Tensorflow."
"The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses."
"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 platform as a service provides user-friendly instruments, making the experience easy."
"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."
 

Cons

"Running this solution requires a minimum of 12GB to 16GB of RAM."
"The tool's MLOps is not good. It's pricing also needs to improve."
"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."
"The solution's initial setup process is complicated."
"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."
"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."
"It would be great if the solution integrated Microsoft Copilot, its AI helper."
"In future releases, I would like to see better integration with Power BI within Microsoft Azure Machine Learning Studio."
"One problem I experience is that switching between multiple accounts can be difficult. I don't think there are any major issues. Mostly, the biggest challenge is to identify business solutions to this. The tool should keep on updating new algorithms and not stay static."
"It would be nice if the product offered more accessibility in general."
 

Pricing and Cost Advice

"The product is expensive."
"I am paying for it following a pay-as-you-go. So, the more I use it, the more it costs."
"There isn’t any such expensive costs and only a standard license is required."
"On a scale from one to ten, with ten being overpriced, I would rate the price of this solution at six."
"The solution cost is high."
"There is a license required for this solution."
"The product's pricing is reasonable."
"Last year, we paid 60,000 for Microsoft Azure Machine Learning Studio in our department."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
33%
Healthcare Company
9%
Manufacturing Company
8%
Computer Software Company
8%
Financial Services Firm
13%
Computer Software Company
10%
Manufacturing Company
10%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Cloudera Data Science Workbench?
I appreciate CDSW's ability to logically segregate environments, such as data, DR, and production, ensuring they don't interfere with each other. The deployment of machine learning is fast and easy...
What needs improvement with Cloudera Data Science Workbench?
The tool's MLOps is not good. It's pricing also needs to improve.
What is your primary use case for Cloudera Data Science Workbench?
We have different use cases. Our banking use case uses machine learning to identify customer life events and recommend the best-suited card products. These machine-learning models are deployed in o...
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

CDSW
Azure Machine Learning, MS Azure Machine Learning Studio
 

Overview

 

Sample Customers

IQVIA, Rush University Medical Center, Western Union
Walgreens Boots Alliance, Schneider Electric, BP
Find out what your peers are saying about Cloudera Data Science Workbench vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: June 2025.
860,168 professionals have used our research since 2012.