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Amazon AWS CloudSearch vs Amazon Athena comparison

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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 Athena
Ranking in Search as a Service
6th
Average Rating
7.8
Reviews Sentiment
7.2
Number of Reviews
11
Ranking in other categories
No ranking in other categories
Amazon AWS CloudSearch
Ranking in Search as a Service
7th
Average Rating
8.4
Number of Reviews
13
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of October 2026, in the Search as a Service category, the mindshare of Amazon Athena is 5.3%, down from 5.5% compared to the previous year. The mindshare of Amazon AWS CloudSearch is 6.4%, down from 7.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Search as a Service Mindshare Distribution
ProductMindshare (%)
Amazon Athena5.3%
Amazon AWS CloudSearch6.4%
Other88.3%
Search as a Service
 

Featured Reviews

YM
Senior Software Engineer at a tech services company with 10,001+ employees
Serverless analytics has reduced daily data query costs and supports accurate financial reporting
The best features Amazon Athena offers are its straightforward framework to perform ad hoc analysis on the data that we have. We use it primarily as our main query engine, so we are not using anything such as Snowflake or similar solutions. We essentially ingest the data into S3 buckets, and then we use Amazon Athena for querying the data. It is our main query platform on AWS. All of our queries, for transformations, are Athena-based queries that are orchestrated via Step Functions. We only pay for the amount of data that we scan. Since we operate on a relatively lower amount of data on a daily basis, we incur a very low cost on our querying. The pay-per-query pricing of Amazon Athena impacts my daily operations significantly. For other query engines, we pay for the query execution time, but in Amazon Athena, you only pay for the amount of data that you have scanned. Our queries primarily filter out the data. Since we operate on a daily basis, we are only concerned with today's data. When querying the data, we automatically put the filter to have the data in today's timestamp only. This way, we incur very low costs compared to other query engines. Our query scans are about 10 to 20 MBs, and despite performing 100 to 150 queries per day, this keeps our costs very manageable. Amazon Athena has positively impacted my organization by providing a completely serverless infrastructure. We have Step Functions, Lambda, and S3 buckets where we store our data. Our main infrastructure is serverless. We wanted a query engine that is less demanding in terms of setup efforts and cost-efficient, so we decided to go with Amazon Athena. It fulfills all our use cases, plus the ACID compliance that it brings, because we use Iceberg on top of Amazon Athena. This ensures our queries and data are consistent, durable, and that the queries are isolated in terms of execution. Athena's ACID compliance, especially with Iceberg, impacts our data consistency and reliability. We apply Iceberg with Parquet, which helps us compress the data to a very good volume. With the applied compression algorithms, we preserve our data consistency during parallel transformations. ACID compliance helps us achieve this, ensuring we do not compromise on our data and that our GDPR for the data is preserved.
HM
Software Developer at ECFY Consulting Private Limited
Search workflows have become faster and our team manages operational records more efficiently
Improvements for Amazon AWS CloudSearch can be made, but I will first start with the biggest improvement. The biggest improvement area is that Amazon AWS CloudSearch feels a little older compared to newer AWS services. The second thing about improvement is the documentation. The documentation could definitely be refreshed with more practical examples and troubleshooting scenarios. During setup, a few indexing issues took longer to diagnose because error messages were pretty generic. Better debugging visibility would reduce trial-and-error work. Monitoring is decent through Amazon CloudWatch, but I would like more detailed search-level diagnostics out of the box. Sometimes it is not obvious why certain queries rank results differently unless you manually test a lot. More transparent query analysis, indexing, and insights would be useful. Logging exists, but deeper visibility would help during optimization.

Quotes from Members

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

Pros

"Amazon Athena has positively impacted my organization by providing a completely serverless infrastructure."
"Athena is serverless, so we don’t have to provision or manage compute clusters, and we can simply point Athena at our data in S3 and run SQL queries immediately."
"Amazon Athena is very stable. I never had any issues with it. The dashboarding tool is okay."
"One of the most valuable features is the ability to partition your databases. I also like the federal query functionality, for cases when you have to query outside your S3 storage, or even completely outside of the AWS platform."
"Athena has a really good UI and is very compatible with on-prem products."
"Amazon Athena's ability to query structured and unstructured data has been beneficial."
"It's easy to set up the product."
"Amazon Athena works for scalability; I query data using tagged data that uses user usage of applications that contain very big data, millions and billions of lines, and it works very well."
"AWS CloudSearch's best features are good performance under high CPU and memory use, and ease of deployment and scaling."
"The best feature is its scalability in that Cloud is always on the fly."
"Amazon AWS CloudSearch is practical and dependable for teams that want managed search without a lot of infrastructure management."
"CDN service reduces latency when accessing our web application."
"The most valuable feature of Amazon AWS CloudSearch is its ability to receive data quickly, and you can access your data easily in a short time."
"The quality of the solution is good."
"It is remarkably efficient and beneficial."
"Storage of photos and files which can be accessed anyplace, anytime, extremely quickly."
 

Cons

"While implementing Amazon Athena, I observed an issue where, even after writing an exclusion pattern on the AWS Glue side, whenever the end user queries, it skips the exclusion pattern, overriding it and directly fetching data from the S3 bucket."
"I use Python to query in Amazon Athena, and it's very complex and difficult just to save Amazon Athena results as an Excel file."
"The solution should include a better API for query services."
"You have to build out the metadata yourself because of the nature of the cloud."
"Transaction support is one of the biggest missing features."
"If you compare it with Palantir, if you have some data and you want to quickly have a look at it, then that feature is not available in Amazon Cloud."
"In terms of its integration capabilities, I would say it's not straightforward. It works, but it's a little bit tricky."
"One improvement I can suggest is that Athena needs to work better with third-parties. For example, the process of querying a Microsoft SQL warehouse could be improved."
"Regarding the period of propagation on CDN servers, sometimes we update photos or files and we don't see the update instantly. We need to wait for sometime, which is quite boring because we may be setting up a marketing campaign which is related to the product's photo and we need to wait to start."
"A reboot should be enhanced."
"Latlon data type only supports single value per document. All other types support multiple values. We faced issues with this because we had scenarios where, for each document, we needed to store multiple latlon values for different geographical locations."
"Security is a concern but they're working on it."
"In terms of what needs improvement, I would say that it needs to keep its cost competitive in the market, especially in comparison to other clouds."
"Amazon's technical support needs to improve as they only solve about half our problems."
"The biggest improvement area is that Amazon AWS CloudSearch feels a little older compared to newer AWS services."
"The solution should improve the recovery aspects that it has on offer."
 

Pricing and Cost Advice

"The solution operates on a serverless model so you only pay for data that you consume."
"Athena is very inexpensive for being a cloud tool."
"I am happy with what they are charging and how they charge it, especially because they charge you per query, and not per series."
"It doesn't cost much if you are already part of the AWS ecosystem."
"On a scale of one to ten, where one point is cheap, and ten points are expensive, I rate the pricing as medium or reasonable."
"We chose AWS because of its cost and stability."
"Amazon AWS CloudSearch charging is based on how many resources you consume or and the solution is known to be a bit expensive."
"In comparison to IBM and Microsoft, the pricing is more favorable."
"I'm not sure how much we pay a year. It might be around $30,000 a year."
"There was no license needed to use this solution."
"Our license costs around $4,000 per month."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Manufacturing Company
12%
Outsourcing Company
10%
Comms Service Provider
7%
Comms Service Provider
12%
Construction Company
11%
Outsourcing Company
10%
Educational Organization
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise3
Large Enterprise4
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise2
Large Enterprise6
 

Questions from the Community

What is your experience regarding pricing and costs for Amazon Athena?
My experience with Amazon Athena regarding pricing, setup costs, and licensing is quite clear after more than three years of usage. I am part of my client's FinOps cloud team, assisting in reducing...
What needs improvement with Amazon Athena?
While implementing Amazon Athena, I observed an issue where, even after writing an exclusion pattern on the AWS Glue side, whenever the end user queries, it skips the exclusion pattern, overriding ...
What is your primary use case for Amazon Athena?
My main use case for Amazon Athena is serving a healthcare organization in the US that needed an interactive SQL editor to write complex queries and retrieve details instead of checking manually in...
What is your experience regarding pricing and costs for Amazon AWS CloudSearch?
We purchased Amazon AWS CloudSearch through the AWS Marketplace. Pricing was understandable once we estimated indexing volume and query traffic. Though it can grow if you scale instances aggressive...
What needs improvement with Amazon AWS CloudSearch?
Improvements for Amazon AWS CloudSearch can be made, but I will first start with the biggest improvement. The biggest improvement area is that Amazon AWS CloudSearch feels a little older compared t...
What is your primary use case for Amazon AWS CloudSearch?
The main use case for us was to search the operational records from our company databases and perform full-text search across operational records and uploaded documents. We needed something where u...
 

Overview

 

Sample Customers

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday
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Find out what your peers are saying about Amazon AWS CloudSearch vs. Amazon Athena and other solutions. Updated: September 2026.
916,212 professionals have used our research since 2012.