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IBM Watson Machine Learning 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

IBM Watson Machine Learning
Ranking in AI Development Platforms
12th
Average Rating
8.0
Reviews Sentiment
7.1
Number of Reviews
7
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
60
Ranking in other categories
Data Science Platforms (5th)
 

Mindshare comparison

As of March 2025, in the AI Development Platforms category, the mindshare of IBM Watson Machine Learning is 1.8%, down from 2.6% compared to the previous year. The mindshare of Microsoft Azure Machine Learning Studio is 7.6%, down from 14.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms
 

Featured Reviews

Anurag Mayank - PeerSpot reviewer
A highly efficient solution that delivers the desired results to its users
I had not considered how the solution could be improved because I was focused on how it was helping me to solve my issues. If I consider how we want to use it in our organization, certain areas of improvement can be addressed. For instance, we want to use it with Generative AI, not like ChatGPT, but in a way intended for industrial use. It would be beneficial to incorporate more AI into the solution.
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 solution is very valuable to our organization due to the fact that we can work on it as a workflow."
"I was particularly interested in trying the AutoML feature to see how it handles data and proposes new models. The variety of models it provides is impressive."
"It is has a lot of good features and we find the image classification very useful."
"We can enable and change developer productivity with artificial intelligence-recommended code based on natural language input or exciting source code."
"Scalability-wise, I rate the solution ten out of ten."
"It has improved self-service and customer satisfaction."
"The most valuable aspect of the solution's the cost and human labor savings."
"The AutoML is helpful when you're starting to explore the problem that you're trying to solve."
"Azure's AutoML feature is probably better than the competition."
"Machine Learning Studio is easy to use."
"When you import the dataset you can see the data distribution easily with graphics and statistical measures."
"The drag-and-drop interface of Azure Machine Learning Studio has greatly improved my workflow."
"​It has helped in reducing the time involved for coding using R and/or Python."
"The interface is very intuitive."
"The most valuable feature is its compatibility with Tensorflow."
 

Cons

"The supporting language is limited."
"Scaling is limited in some use cases. They need to make it easier to expand in all aspects."
"Honestly, I haven't seen any comparative report that has run the same data through two different artificial intelligence or machine learning capabilities to get something out of it. I would love to see that."
"In future releases, I would like to see a more flexible environment."
"They should add more GPU processing power to improve performance, especially when dealing with large amounts of data."
"Sometimes training the model is difficult."
"If I consider how we want to use it in our organization, certain areas of improvement can be addressed. For instance, we want to use it with Generative AI, not like ChatGPT, but in a way intended for industrial use."
"Operability with R could be improved."
"I have found Databricks is a better solution because it has a lot of different cluster choices and better integration with MLflow, which is much easier to handle in a machine learning system."
"Easier customization and configuration would be beneficial."
"Microsoft Azure Machine Learning Studio could improve by adding pixel or image analysis. This is a priority for me."
"Integration with social media would be a valuable enhancement."
"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice."
"The product must improve its documentation."
"n the solution, there is the concept of workspaces, and there is no means to share the computing infrastructure across those workspaces."
 

Pricing and Cost Advice

"The pricing model is good."
"I've only been using the free tier, but it's quite competitive on a service basis."
"ML Studio's pricing becomes a numbers game."
"I am paying for it following a pay-as-you-go. So, the more I use it, the more it costs."
"I would rate the pricing an eight out of ten, with ten being very expensive. Not very expensive, not very cheap."
"The solution cost is high."
"The solution operates on a pay-per-use model."
"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."
"I rate the solution's pricing a four on a scale of one to ten, where one is cheap, and ten is expensive."
"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."
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Top Industries

By visitors reading reviews
Computer Software Company
16%
Educational Organization
12%
Financial Services Firm
11%
University
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
No data available
 

Questions from the Community

What do you like most about IBM Watson Machine Learning?
I was particularly interested in trying the AutoML feature to see how it handles data and proposes new models. The variety of models it provides is impressive.
What needs improvement with IBM Watson Machine Learning?
Sometimes training the model is difficult. We need to have at least a few different components to evaluate and understand the behavior of different users to have a very, very high accuracy in the m...
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 IBM Watson Machine Learning vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: March 2025.
842,651 professionals have used our research since 2012.