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

Domino Data Science Platform 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

Domino Data Science Platform
Ranking in Data Science Platforms
15th
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
2
Ranking in other categories
No ranking in other categories
Microsoft Azure Machine Lea...
Ranking in Data Science Platforms
5th
Average Rating
7.6
Reviews Sentiment
7.0
Number of Reviews
60
Ranking in other categories
AI Development Platforms (3rd)
 

Mindshare comparison

As of March 2025, in the Data Science Platforms category, the mindshare of Domino Data Science Platform is 2.5%, down from 2.8% compared to the previous year. The mindshare of Microsoft Azure Machine Learning Studio is 5.3%, down from 9.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

AS
Accelerated machine learning model development with seamless deployment
We used Domino Data Science Platform for developing and working with machine learning models. It facilitated end-to-end development processes. Domino is based on Git, enabling collaboration similar to using Git. Each user operates on their own equivalent of a branch or fork, and once finished, they…
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

"The scalability of the solution is good; I'd rate it four out of five."
"The workspaces, which are like wrappers of Docker containers, made it easy to start development environments using Domino."
"MLS allows me to set up data experiments by running through various regression and other machine learning algorithms, with different data cleaning and treatment tools. All of this can be achieved via drag and drop, and a few clicks of the mouse."
"Azure's AutoML feature is probably better than the competition."
"The solution is integrated with our Microsoft Azure tenant, and we don't have to go anywhere else outside the tenant."
"The product's standout feature is a robust multi-file network with limited availability."
"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."
"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."
"Regarding the technical support for the solution, I find the documentation provided comprehensive and helpful."
"The most valuable feature is data normalization."
 

Cons

"The predictive analysis feature needs improvement."
"The deployment of large language models (LLMs) could be improved."
"Stability-wise, you may face certain problems when you fail to refresh the data in the solution."
"The initial setup time of the containers to run the experiment is a bit long."
"When you use different Microsoft tools, there are different pricing metrics. It doesn't make sense. The pricing metrics are quire difficult to understand and should be either clarified or simplified. It would help us sell the solution to customers."
"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."
"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."
"Integration with social media would be a valuable enhancement."
"The regulatory requirements of the product need improvement."
 

Pricing and Cost Advice

Information not available
"ML Studio's pricing becomes a numbers game."
"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 cost is high."
"On a scale from one to ten, with ten being overpriced, I would rate the price of this solution at six."
"The product is not that expensive."
"Last year, we paid 60,000 for Microsoft Azure Machine Learning Studio in our department."
"It is less expensive than one of its competitors."
"The platform's price is low."
report
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
842,194 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
35%
Manufacturing Company
11%
Insurance Company
9%
Computer Software Company
7%
Financial Services Firm
13%
Computer Software Company
11%
Manufacturing Company
10%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What needs improvement with Domino Data Science Platform?
The deployment of large language models (LLMs) could be improved. Currently, Domino provides a simple server that cannot handle big deployments, which is not suitable for LLMs.
What is your primary use case for Domino Data Science Platform?
We used Domino Data Science Platform for developing and working with machine learning models. It facilitated end-to-end development processes. Domino is based on Git, enabling collaboration similar...
What advice do you have for others considering Domino Data Science Platform?
It's important to have a DevOps team well-versed with cloud-native solutions to manage Domino effectively. Relying solely on data scientists might not be sufficient. I'd rate the solution eight out...
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

Domino Data Lab Platform
Azure Machine Learning, MS Azure Machine Learning Studio
 

Interactive Demo

Demo not available
 

Overview

 

Sample Customers

Allstate, GSK, AstraZeneca, Federal Reserve, US Navy, Bristol Myers Squibb, Bayer, BNP Paribas, Moodys, New York Life
Walgreens Boots Alliance, Schneider Electric, BP
Find out what your peers are saying about Domino Data Science Platform vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: March 2025.
842,194 professionals have used our research since 2012.