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Amazon Athena vs Amazon Kendra comparison

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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 Kendra
Ranking in Search as a Service
8th
Average Rating
7.6
Reviews Sentiment
7.1
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of September 2026, in the Search as a Service category, the mindshare of Amazon Athena is 5.3%, down from 5.9% compared to the previous year. The mindshare of Amazon Kendra is 6.2%, down from 9.6% 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 Kendra6.2%
Other88.5%
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.
AM
Architect at IGT Solutions
Kendra has a nice AI built-in, enhancing the search experience and highly stable solution
There are many valuable features. For example, there are many documents that contain a lot of legal information. So we want to understand whether all the documents have the required complaint-related information or not, and whether they are following the standard policies of documentation. We have multiple documents, so we don't know which document has the sought-after information. Therefore, we want to perform an enterprise search on it. So there are a lot of use cases we are trying to build using these newer technologies, specifically Kendra. Moreover, Kendra has AI, which has an upper edge, and that is really helpful. It has a nice AI inbuilt, which improves the search part of it.

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."
"The solution is very easy to use and integrations are very smooth."
"Amazon Athena is very stable. I never had any issues with it. The dashboarding tool is okay."
"Athena has a really good UI and is very compatible with on-prem products."
"After implementing Amazon Athena in our project, we have observed significant savings in cost structure and effort, and the end user is very happy and is conducting analytical work using Amazon Athena."
"The best feature of Amazon Athena is that we can use Glue to build the schema from the data and then we can query the data directly on S3."
"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."
"It's easy to set up the product."
"Provides flexibility to tune the relevance and ranking of results."
"Until recently, there wasn't an out-of-the-box service in the market for enterprise documents like Kendra."
"We have good use cases where stability is everything. So it's a stable solution."
 

Cons

"Transaction support is one of the biggest missing features."
"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."
"Amazon Athena can be improved, especially when working with S3 tables, which is a caveat for us."
"I think it would be better if the product were more mature. It's still a young product compared to Power BI or Qlik. I find that development is a bit difficult, but it might be because I'm used to other tools. The dashboarding capabilities could be better. The reporting and statement generation could be better. I couldn't technically initiate picture-perfect reporting, for example, to send out statements every month for banking customers."
"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."
"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."
"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."
"This is a really, really expensive solution making the adoption of it very difficult at the enterprise level."
"There are some token limits."
"The time it takes for indexing documents could be reduced."
 

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."
"It doesn't cost much if you are already part of the AWS ecosystem."
"I am happy with what they are charging and how they charge it, especially because they charge you per query, and not per series."
"The pricing falls in the medium range."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Manufacturing Company
12%
Outsourcing Company
10%
Healthcare Company
7%
Financial Services Firm
16%
Computer Software Company
14%
Manufacturing Company
13%
Comms Service Provider
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise3
Large Enterprise4
No data available
 

Questions from the Community

What needs improvement with Amazon Athena?
Amazon Athena can be improved, especially when working with S3 tables, which is a caveat for us. It does not work very well with Amazon Athena, as we have to do multiple settings in terms of provid...
What is your primary use case for Amazon Athena?
My main use case for Amazon Athena is querying data that sits in S3 buckets. Currently, I am working for an aviation client for which we receive data on a daily basis. We take this data from a sour...
What advice do you have for others considering Amazon Athena?
Regarding Amazon Athena's AI capabilities, we do not utilize them. However, data governance is ensured, and security is adequate since we operate within the VPC. ACID compliance helps preserve GDPR...
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Overview

 

Sample Customers

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday
Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
Find out what your peers are saying about Amazon Athena vs. Amazon Kendra and other solutions. Updated: September 2026.
913,806 professionals have used our research since 2012.