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Darwin 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:
 

ROI

Sentiment score
6.2
Companies find Darwin efficient, preventing revenue loss and enhancing machine learning, with returns two to three times higher.
Sentiment score
6.6
Microsoft Azure Machine Learning Studio offers improved efficiency and dataset summarization, with varying ROI perspectives and a 7/10 rating.
 

Customer Service

Sentiment score
8.4
Darwin's support is highly responsive and efficient, quickly resolving issues and providing valuable guidance, ensuring customer satisfaction.
Sentiment score
7.2
Microsoft Azure Machine Learning Studio's customer service is praised for responsiveness but satisfaction varies, with larger clients receiving better support.
Microsoft technical support is rated a seven out of ten.
 

Scalability Issues

Sentiment score
6.7
Darwin scales well with challenges on large datasets; plans for expansion need internal changes for wider departmental adoption.
Sentiment score
7.3
Microsoft Azure Machine Learning Studio offers efficient scalability for various user bases, with potential improvements for complex deployments.
We are building Azure Machine Learning Studio as a scalable solution.
 

Stability Issues

Sentiment score
7.0
Darwin's stability has improved, boasting 99% availability, though some issues persist; support is responsive, yet enhancements continue.
Sentiment score
7.8
Microsoft Azure Machine Learning Studio is stable and reliable, with minor issues and concerns about classic version retirement.
 

Room For Improvement

Darwin users seek API integration, improved functionality, educational resources, and better automation for precision and transparency in AI processes.
Microsoft Azure Machine Learning Studio could enhance usability, expand features, improve integration, and provide clearer pricing with better support.
I find the pricing to be not a good story in this case, as it is not affordable for everyone.
In future updates, I would appreciate improvements in integration and more AI features.
 

Setup Cost

Darwin's licensing costs are significant yet often seen as valuable, with predictable setup fees and optional costs for integrations.
Microsoft Azure Machine Learning Studio offers flexible pricing from $20 monthly, but users find cost complexity challenging.
I rate the pricing as three or four on a scale of one to ten in terms of affordability.
 

Valuable Features

Darwin excels in data cleaning, model-building, and integration, enhancing productivity and accessibility for non-experts in machine learning.
Microsoft Azure Machine Learning Studio offers user-friendly features including AutoML, scalability, and integration for seamless team collaboration and deployment.
Azure Machine Learning Studio provides a platform to integrate with large language models.
Machine Learning Studio is easy to use, with a significant feature being the drag and drop interface that enhances workflow without any complaints.
 

Categories and Ranking

Darwin
Ranking in Data Science Platforms
27th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
8
Ranking in other categories
No ranking in other categories
Microsoft Azure Machine Lea...
Ranking in Data Science Platforms
4th
Average Rating
7.6
Reviews Sentiment
7.0
Number of Reviews
60
Ranking in other categories
AI Development Platforms (3rd)
 

Mindshare comparison

As of January 2025, in the Data Science Platforms category, the mindshare of Darwin is 0.3%, down from 0.3% compared to the previous year. The mindshare of Microsoft Azure Machine Learning Studio is 5.7%, down from 10.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

AC
Empowers SMEs to build solutions and interface them with the existing business systems, products and workflows.
There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do. Because it's so much better than traditional methods, we don't get a ton of complaints of, "Oh, we wish we could do that." Most people are happy to see that they can build models that quickly, and that it can be done by the people who actually understand the problem, i.e. SMEs, rather than having to rely on data scientists. There's a small learning curve, but it's shorter for an SME in a given industry to learn Darwin than it takes for data scientists to learn industry-specific problems. The industry I work in deals with tons and tons of data and a lot of it lends itself to Darwin-created solutions. Initially, there were some limitations around the size of the datasets, the number of rows and number of columns. That was probably the biggest challenge. But we've seen the Darwin product, over time, slowly remove those limitations. We're happy with the progress they've made.
HéctorGiorgiutti - PeerSpot reviewer
Requires minimal maintenance, is scalable, and stable
The initial setup depends on the developer's knowledge of machine learning models as to whether it is easy or difficult. With a good understanding of these models, then we can get to work quickly in the environment. With 20 years of experience in IT, making applications on legacy platforms and non-web platforms, I have found that Azure has a very good implementation. The platform is so comprehensive that it doesn't matter what kind of work we do, we can find the tools needed to get the job done. In comparison to what I was doing five years ago, Azure is a great platform and I really enjoy working with it. We should allocate up to 12 percent of our project time to deployment. Depending on the complexity of the solution, we should expect to spend more time on deployment.
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Top Industries

By visitors reading reviews
Computer Software Company
25%
Real Estate/Law Firm
15%
Financial Services Firm
13%
Educational Organization
11%
Financial Services Firm
12%
Computer Software Company
10%
Manufacturing Company
9%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

Ask a question
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?
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

Hunt Oil, Hitachi High-Tech Solutions
Walgreens Boots Alliance, Schneider Electric, BP
Find out what your peers are saying about Darwin vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: January 2025.
831,158 professionals have used our research since 2012.