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Amazon Comprehend vs Microsoft Azure Machine Learning Studio comparison

 

Comparison Buyer's Guide

Executive Summary

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

Amazon Comprehend
Ranking in Data Science Platforms
19th
Average Rating
8.0
Reviews Sentiment
7.4
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
7.6
Reviews Sentiment
7.0
Number of Reviews
61
Ranking in other categories
AI Development Platforms (3rd)
 

Mindshare comparison

As of April 2025, in the Data Science Platforms category, the mindshare of Amazon Comprehend is 0.5%, down from 0.8% compared to the previous year. The mindshare of Microsoft Azure Machine Learning Studio is 5.3%, down from 9.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

Ashish Lata - PeerSpot reviewer
Integration with automation tools enhances customer sentiment analysis
Comprehend is a useful service for sentiment analysis as it analyzes customer transcripts to evaluate interactions between customers and agents. It provides scores indicating whether sentiments are positive, negative, or neutral. The integration with AWS services like DynamoDB and Lambda facilitates automated analysis, contributing to more informed assessments of customer interactions.
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

"Amazon Comprehend works with a large pool of doctors. They're building the product based on working with domain experts."
"I am totally happy with AWS support, as they provide excellent solutions."
"ML Studio is very easy to maintain."
"The solution is very easy to use, so far as our data scientists are concerned."
"The solution is really scalable."
"The visualizations are great. It makes it very easy to understand which model is working and why."
"The solution is easy to use and has good automation capabilities in conjunction with Azure DevOps."
"The drag-and-drop interface of Azure Machine Learning Studio has greatly improved my workflow."
"Regarding the technical support for the solution, I find the documentation provided comprehensive and helpful."
"It is very easy to test different kinds of machine-learning algorithms with different parameters. You choose the algorithm, drag and drop to the workspace, and plug the dataset into this component."
 

Cons

"It is a bit complex to scale. It is still evolving as a product."
"There is room for improvement in terms of accuracy. For example, when a sentence expresses a negative sentiment, such as 'I want to cancel my credit card,' it is crucial for the system to accurately identify it as negative."
"The price of the solution has room for improvement."
"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice."
"The solution cannot connect to private block storage."
"The solution's initial setup process is complicated."
"It would be great if the solution integrated Microsoft Copilot, its AI helper."
"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."
"Using the solution requires some specific learning which can take some time."
"The solution should be more customizable. There should be more algorithms."
 

Pricing and Cost Advice

Information not available
"There isn’t any such expensive costs and only a standard license is required."
"The pricing for Microsoft products can be complex due to changes and being cloud-based, so it's not straightforward. I've been familiar with it for years, but sometimes details about product licenses and distribution can be unclear. For Microsoft Azure Machine Learning Studio specifically, I would rate the price a six out of ten."
"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."
"From a developer's perspective, I find the price of this solution high."
"To use MLS is fairly cheap. Even the paid account is something like $20/month, unless you are provisioning large numbers of VMs for a Hadoop cluster. The main MS makes money with this solution is forcing the user to deploy their model on REST API, and being charged each time the API is accessed. There are several pricing tiers for the API. If you do not use the API, then value of MLS is to create rapid experiments ($20/month). The resulting model is not exportable to use, thus you’ll have to recreate the algorithms in either R or Python, which is what I did. MLS results gave me a direction to work with, the actual work is mostly done in R and Python outside of MLS."
"The platform's price is low."
"There is a lack of certainty with the solution's pricing."
"There is a license required for this solution."
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Top Industries

By visitors reading reviews
No data available
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 needs improvement with Amazon Comprehend?
Regarding improvements, I would focus on accuracy. For example, if a customer says, 'I want to cancel my credit card,' it should clearly be identified as a negative sentiment. Improving accuracy in...
What is your primary use case for Amazon Comprehend?
I have used Amazon Comprehend primarily for sentiment analysis in my project. I analyze customer transcripts to determine if they are satisfied with the agents they interact with. I store the trans...
What advice do you have for others considering Amazon Comprehend?
I would rate Amazon Comprehend an eight out of ten because there is always room for improvement, especially in terms of accuracy. For those new to Comprehend, understanding its usage and reviewing ...
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

LexisNexis, Vibes, FINRA, VidMob
Walgreens Boots Alliance, Schneider Electric, BP
Find out what your peers are saying about Amazon Comprehend vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: April 2025.
848,989 professionals have used our research since 2012.