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Amazon Comprehend vs Azure Databricks 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
22nd
Average Rating
8.0
Reviews Sentiment
7.4
Number of Reviews
2
Ranking in other categories
No ranking in other categories
Azure Databricks
Ranking in Data Science Platforms
20th
Average Rating
8.0
Reviews Sentiment
3.7
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Featured Reviews

Ashish Lata - PeerSpot reviewer
Professional Freelancer at Open for all
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.
VishnuReddy2 - PeerSpot reviewer
Consulting Enterprise Architect at R2V2.ai
Unified data platform has supported real-time analytics and advanced machine learning workflows
The real-time processing with Azure Databricks is supported through integration from external systems, for which we have to go with tools such as Matillion's HVR or Kafka. I have experience using HVR, high-volume replication. You get real-time data replicated into Azure Databricks using these tools. When looking for performance metrics in Azure Databricks, it depends on the processing. It can process millions of records quickly, and it is driven by the Spark framework, which is pretty strong in terms of framework perspective. The columnar database is another strong feature which helps enhance its performance. Prior to the introduction of Unity Catalog, there was no metadata capability in Azure Databricks. It was very simplistic, but now with the Unity Catalog introduction and Delta Sharing capabilities, Azure Databricks is at the top-notch at this point in time. In comparison, SAP BW is a little bit more mature because apart from RBAC, it gives data-level authorization, which is a little bit not that great in Azure Databricks at this point in time.

Quotes from Members

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

Pros

"I am totally happy with AWS support, as they provide excellent solutions."
"Amazon Comprehend works with a large pool of doctors. They're building the product based on working with domain experts."
"The best features in Azure Databricks for me are that it's easy to use, flexible, and has fast processing, and you can use multiple data types."
"Regarding the learning curve, it is a good technology; it is the first time I am working on a cloud platform, and before that, I have not worked on any data engineering tool that is on cloud, so it is good learning."
"Azure Databricks gives the capability to handle a lot of big data use cases and machine learning use cases, but machine learning use cases need quite a lot of compute power, and that is where the cost spikes up."
 

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."
"At this point, I cannot comment on the cost being ideal; it is on the higher side, but in the cloud-based environment, compared to on-premise, it could be far lesser in cost."
"I have given the product a rating of six out of ten just because I do not use all of the functionalities, and I see some direction for improvement as well; also, every product has something to improve, and I have not used many features in this product."
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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 ...
What is your experience regarding pricing and costs for Azure Databricks?
Regarding the licensing cost of Azure Databricks, it has evolved quite a lot. The compute is the biggest cost, as with any other big data solutions. The storage cost is almost minimal or negligible...
What needs improvement with Azure Databricks?
Overall, my experience has been positive with Azure Databricks; they have many features, but there is no use case for me to use those features, such as Delta Live Tables and Genie. In my opinion, I...
What is your primary use case for Azure Databricks?
The primary use cases for me are the reportings I have to do, so I need to ingest data from the file and create reports. I do not utilize it for real-time data processing. I have not integrated Azu...
 

Overview

 

Sample Customers

LexisNexis, Vibes, FINRA, VidMob
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Find out what your peers are saying about Amazon Comprehend vs. Azure Databricks and other solutions. Updated: March 2026.
884,873 professionals have used our research since 2012.