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Microsoft Azure Machine Learning Studio vs SAS Enterprise Miner 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

Microsoft Azure Machine Lea...
Ranking in Data Science Platforms
4th
Average Rating
7.6
Reviews Sentiment
7.0
Number of Reviews
61
Ranking in other categories
AI Development Platforms (3rd)
SAS Enterprise Miner
Ranking in Data Science Platforms
18th
Average Rating
7.6
Reviews Sentiment
6.2
Number of Reviews
13
Ranking in other categories
Data Mining (7th)
 

Mindshare comparison

As of April 2025, in the Data Science Platforms category, the mindshare of Microsoft Azure Machine Learning Studio is 5.3%, down from 9.4% compared to the previous year. The mindshare of SAS Enterprise Miner is 0.7%, down from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

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…
reviewer1352853 - PeerSpot reviewer
A stable product that is easy to deploy and can be used for structured and unstructured data mining
We use the solution for predictive analytics to do structured and unstructured data mining I like the way the product visually shows the data pipeline. The product must provide better integration with cloud-native technologies. I have been using the solution for 20 years. The product is very…

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Auto email and studio are great features."
"Regarding the technical support for the solution, I find the documentation provided comprehensive and helpful."
"The solution is very easy to use, so far as our data scientists are concerned."
"In terms of what I found most valuable in Microsoft Azure Machine Learning Studio, I especially love the designer because you can just drag and drop items there and apply the logic that's already available with the designer. I love that I can use the libraries in Microsoft Azure Machine Learning Studio, so I don't have to search for the algorithms and all the relevant libraries because I can see them directly on the designer just by dragging and dropping. Though there's a bit of work during data cleansing, that's normal and can't be avoided. At least it's easy to find the relevant algorithm, apply that algorithm to the data, then get the desired output through Microsoft Azure Machine Learning Studio. I also like the API feature of the solution which is readily available for me to expose the output to any consuming application, so that takes out a lot of headache. Otherwise, I have to have a developer who knows the API, and I have to have an API app, so all that is completely taken care of by the Microsoft Azure Machine Learning Studio designer. With the solution, I can concentrate on how to improve the data quality to get quality recommendations, so this lets me concentrate on my job rather than focusing on the regular development of APIs or the pipelines, in particular, the data pipelines pulling the data from other sources. All the data is taken care of and you can also concentrate on other required auxiliary activities rather than just concentrating on machine learning."
"The product is well organized. The thing is how we will get the models to work within our code. We have some suggestions there, but we want to gain more experience and be ready to answer that because we are currently working on this and don't have all the answers yet. The tool is well organized. What I am very happy about is the ease of deploying new resources. You can easily create your pipeline within minutes."
"The platform as a service provides user-friendly instruments, making the experience easy."
"Machine Learning Studio is easy to use, with a significant feature being the drag and drop interface that enhances workflow without any complaints."
"It's easy to deploy."
"The most valuable feature is the decision tree creation."
"I like the way the product visually shows the data pipeline."
"The technical support is very good."
"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."
"The solution is very good for data mining or any mining issues."
"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
"he solution is scalable."
"Good data management and analytics."
 

Cons

"The interface is a bit overloaded."
"Performance is very poor."
"The speed of deployment should be faster, as should testing."
"In terms of data capabilities, if we compare it to Google Cloud's BigQuery, we find a difference. When fetching data from web traffic, Google can do a lot of processing with small queries or functions."
"Improvement in integration is crucial, and it'll be interesting to see how it develops, especially with SAP's move towards cloud-based solutions like SAP Rise and its collaboration with hyper scalers like AWS. Integrating SAP with hyperscaler machine learning solutions could simplify operations, although SAP's environment is complex. SAP has initiated deals with AWS for this purpose, but I'm not as familiar with Microsoft Azure Machine Learning Studio's involvement."
"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."
"The pricing policy should 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."
"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."
"The solution is much more complex than other options."
"The initial setup is challenging if doing it for the first time."
"The product must provide better integration with cloud-native technologies."
"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"The user interface of the solution needs improvement. It needs to be more visual."
"Virtualization could be much better."
 

Pricing and Cost Advice

"The solution cost is high."
"It is less expensive than one of its competitors."
"The licensing cost is very cheap. It's less than $50 a month."
"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."
"From a developer's perspective, I find the price of this solution high."
"The product is not that expensive."
"I rate the solution's pricing a four on a scale of one to ten, where one is cheap, and ten is expensive."
"The solution operates on a pay-per-use model."
"This solution is for large corporations because not everybody can afford it."
"The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."
"The solution must improve its licensing models."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
10%
Manufacturing Company
10%
Healthcare Company
6%
Financial Services Firm
25%
University
12%
Educational Organization
10%
Manufacturing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

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.
What do you like most about SAS Enterprise Miner?
I like the way the product visually shows the data pipeline.
What is your experience regarding pricing and costs for SAS Enterprise Miner?
The solution must improve its licensing models. It bundles all the products into smaller products. We can only have a subset of the functionality available according to our license. I rate the pric...
What needs improvement with SAS Enterprise Miner?
The product must provide better integration with cloud-native technologies.
 

Also Known As

Azure Machine Learning, MS Azure Machine Learning Studio
Enterprise Miner
 

Overview

 

Sample Customers

Walgreens Boots Alliance, Schneider Electric, BP
Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare
Find out what your peers are saying about Microsoft Azure Machine Learning Studio vs. SAS Enterprise Miner and other solutions. Updated: April 2025.
849,190 professionals have used our research since 2012.