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Amazon Comprehend vs Amazon SageMaker 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
Amazon SageMaker
Ranking in Data Science Platforms
3rd
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
36
Ranking in other categories
AI Development Platforms (4th)
 

Mindshare comparison

As of March 2025, in the Data Science Platforms category, the mindshare of Amazon Comprehend is 0.5%, down from 0.9% compared to the previous year. The mindshare of Amazon SageMaker is 7.5%, down from 9.9% 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.
Hemant Paralkar - PeerSpot reviewer
Improves team collaboration with advanced feature sharing but needs a better user experience
Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker. This would empower citizen data scientists to utilize the tool more effectively since many data scientists do not have a core development background. Additionally, dealing with frequent UI updates can be challenging, especially for infrastructure architects like myself. It involves effort to migrate to new UIs, making the updates not seamless. User auditing requires enhancements as tracking operations performed by users can be difficult due to dynamic IP validation and role propagation.

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."
"The most tool's valuable feature, in my experience, is hyperparameter tuning. It allows us to test different parameters for the same model in parallel, which helps us quickly identify the configuration that yields the highest accuracy. This parallel computing capability saves us a lot of time."
"They are doing a good job of evolving."
"The support is very good with well-trained engineers whose training curriculum is rigorous."
"The deployment is very good, where you only need to press a few buttons."
"The most valuable features are the ability to store artifacts and gather reports and measures from experiments."
"The technical support of the tool was good."
"SageMaker supports building, training, and deploying AI models from scratch, which is crucial for my ML project."
"SageMaker offers functionalities like Jupyter Notebooks for development, built-in algorithms, model tuning, and options to deploy models on managed infrastructure."
 

Cons

"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."
"It is a bit complex to scale. It is still evolving as a product."
"Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker."
"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."
"Amazon might need to emphasize its capabilities in generative models more effectively."
"The dashboard could be improved by including more features and providing more information about deployed models, their drift, performance, scaling, and customization options."
"Lacking in some machine learning pipelines."
"The main challenge with Amazon SageMaker is the integrations."
"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."
"While integration is available, there are concerns about how secure this integration is, particularly when exposing data to SageMaker."
 

Pricing and Cost Advice

Information not available
"I rate the pricing a five on a scale of one to ten, where one is the lowest price, and ten is the highest price. The solution is priced reasonably. There is no additional cost to be paid in excess of the standard licensing fees."
"The pricing is complicated as it is based on what kind of machines you are using, the type of storage, and the kind of computation."
"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a six out of ten."
"You don't pay for Sagemaker. You only pay for the compute instances in your storage."
"On average, customers pay about $300,000 USD per month."
"The pricing is comparable."
"The tool's pricing is reasonable."
"The solution is relatively cheaper."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
18%
Educational Organization
14%
Computer Software Company
11%
Manufacturing Company
9%
 

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 ...
How would you compare Databricks vs Amazon SageMaker?
We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...
What do you like most about Amazon SageMaker?
We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for t...
What is your experience regarding pricing and costs for Amazon SageMaker?
Before deploying SageMaker, I reviewed the pricing, especially for notebook instances. The cost for small to medium instances is not very high.
 

Also Known As

No data available
AWS SageMaker, SageMaker
 

Overview

 

Sample Customers

LexisNexis, Vibes, FINRA, VidMob
DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit
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