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Amazon Comprehend vs Google Cloud Datalab 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
7.5
Number of Reviews
1
Ranking in other categories
No ranking in other categories
Google Cloud Datalab
Ranking in Data Science Platforms
16th
Average Rating
7.8
Reviews Sentiment
6.4
Number of Reviews
6
Ranking in other categories
Data Visualization (19th)
 

Mindshare comparison

As of February 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 Google Cloud Datalab is 0.9%, down from 1.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

Pavan Nanjundappa - PeerSpot reviewer
Good job extracting entities and does the classification in the healthcare products
I would like to see a feature that allows me to create or generate a summary based on the extracted entities. Amazon Comprehend works with a large pool of doctors. They're building the product based on working with domain experts. I don't have any suggestions except if they can provide a feature for generating the summary for the entities that has been updated.
Nilesh Gode - PeerSpot reviewer
Easy to setup, stable and easy to design data pipelines
The scalability is average. We have not faced any issues with scalability. There are more than 500 end users using this solution in our company. It is an integral part of the daily operations. The usage pattern is not a one-time thing; employees regularly access and utilize the application. We use it at a global level with a scattered user base. This means that users don't all use the application at the same time. So, around 300 out of 500 employees use the solution, and this usage is spread out throughout the day.

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."
"For me, it has been a stable product."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"The APIs are valuable."
"Google Cloud Datalab is very customizable."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"All of the features of this product are quite good."
 

Cons

"It is a bit complex to scale. It is still evolving as a product."
"We have also encountered challenges during our transition period in terms of data control and segmentation. The management of each channel and data structure as it has its own unique characteristics requires very detailed and precise control. The allocation should be appropriate and the complexity increases due to the different time zones and geographic locations of our clients. The process usually involves migrating the existing database sets to gcp and ensure data integrity is maintained. This is the only challenge that we faced while navigating the integers of the solution and honestly it was an interesting and unique experience."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"The interface should be more user-friendly."
"There is room for improvement in the graphical user interface. So that the initial user would use it properly, that would be a good option."
"Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated."
"The product must be made more user-friendly."
 

Pricing and Cost Advice

Information not available
"The pricing is quite reasonable, and I would give it a rating of four out of ten."
"It is affordable for us because we have a limited number of users."
"The product is cheap."
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Top Industries

By visitors reading reviews
Manufacturing Company
12%
Financial Services Firm
10%
University
9%
Healthcare Company
9%
Financial Services Firm
19%
Computer Software Company
14%
University
10%
Manufacturing Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

What needs improvement with Amazon Comprehend?
I would like to see a feature that allows me to create or generate a summary based on the extracted entities. Amazon Comprehend works with a large pool of doctors. They're building the product base...
What is your primary use case for Amazon Comprehend?
I use it to extract medical entities for doctors like the deceased and so on. It does the job well for our requirements. It is mainly for automation.
What advice do you have for others considering Amazon Comprehend?
Overall, I would rate the product an eight out of ten. I would recommend Amazon AWS Medical Comprehend for healthcare products because it does a good job extracting entities and does the classifica...
What do you like most about Google Cloud Datalab?
Google Cloud Datalab is very customizable.
What needs improvement with Google Cloud Datalab?
Access is always via URL, and unless your network is fast, it would be a little tough in India. In India, if we had a faster network, it would be easier. In a big data environment, like when forcin...
What is your primary use case for Google Cloud Datalab?
It's for our daily data processing, and there's a batch job that executes it. The process involves more than ten servers or systems. Some of them use a mobile network, some are ONTAP networks, and ...
 

Overview

 

Sample Customers

LexisNexis, Vibes, FINRA, VidMob
Information Not Available
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