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Amazon Athena vs Azure AI Search 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 Athena
Ranking in Search as a Service
6th
Average Rating
7.8
Reviews Sentiment
7.2
Number of Reviews
9
Ranking in other categories
No ranking in other categories
Azure AI Search
Ranking in Search as a Service
4th
Average Rating
7.4
Number of Reviews
9
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of January 2026, in the Search as a Service category, the mindshare of Amazon Athena is 5.5%, down from 12.4% compared to the previous year. The mindshare of Azure AI Search is 9.0%, down from 14.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Search as a Service Market Share Distribution
ProductMarket Share (%)
Azure AI Search9.0%
Amazon Athena5.5%
Other85.5%
Search as a Service
 

Featured Reviews

Ciro Baldim Guerra - PeerSpot reviewer
Sr Analytics Engineer at Itau Unibanco S.A.
Have struggled with exporting complex data and have disabled code suggestions due to inefficiency
I think there is room for improvement in Amazon Athena, and the first thing I will put is the data output. 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 only option is copying the data, but sometimes if it exceeds 100 lines, if you copy and paste in Excel, it's very bad. You can't copy above 100 lines. The other option is downloading a CSV file, but the CSV file is not UTF-8 Unicode. Here in Brazil, we speak Portuguese, and there are a lot of special characters in the words and even names, and everything gets garbled when you put it in a CSV. You have to decode, encode, and there are a lot of problems. It could easily save as an Excel file since there are a lot of engines to help with it, so an XLSX file extension could be this way. Another point I would mention is the word completion. When I'm coding and making statements and queries, Amazon Athena tries to help me write the code, and that's very problematic. Sometimes I'm using some tables that I use every day, and Amazon Athena doesn't get the tables I'm using and suggests very improbable data. I have access to more than 30 databases and hundreds of tables. So, I turn it off, I disable the word completion because when I'm coding, the word completion makes the coding slower. It's very difficult, and every time I have to press escape to skip the completion. It's very ineffective, so I disable it because in other applications it functions very well, such as VS Code.
Prabakaran SP - PeerSpot reviewer
Software Architect at a financial services firm with 1-10 employees
Automated indexing has streamlined document search workflows but semantic relevance and setup complexity still need improvement
We used the semantic search capabilities of Azure AI Search, but we haven't gotten good results in the semantic search. So we are exploring with ChromaDB, and Cosmos is having the capability of doing the semantic search as well. We are exploring that. A few queries we use analytics search, which works and is good. Analytics search is good. We are trying the ML capabilities of the product since we are using Databricks and other tools for building the models, MLflow, and related items. We are still working on proof of concepts, which could be better with ChromaDB or Cosmos or vector search or inbuilt Databricks vector stores. Language processing is not about user intention; it's about the context. If there is a document and you want to know the context of a particular section, then we would use vector search. Instead of traversing through the whole document, while chunking it into the vector, we'll categorize and chunk, and then we'll look only at those chunks to do a semantic search. When comparing Azure AI Search, I'm doing a proof of concept because with ChromaDB I can create instances using LangChain anywhere. For per session, I can create one ChromaDB and can remove it, which is really useful for proof of concepts. Instead of creating an Azure AI Search instance and doing that there, that is one advantage I'm seeing for the proof of concept alone, not for the entire product. I hope it should support all the embedding providers as well. Is there a viewer or tool similar to Storage Explorer? We are basically SQL-centric people, so we used to find Cosmos DB very quick for us when we search something and create indexes. I guess there is some limitation in Azure AI Search. I couldn't remember now, such as querying limitations. I'm not remembering that part.

Quotes from Members

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

Pros

"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."
"It's easy to set up the product."
"Athena has a really good UI and is very compatible with on-prem products."
"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."
"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."
"Creates indexers to get data from different data sources."
"The product is extremely configurable, allowing you to customize the search experience to suit your needs."
"The solution's initial setup is straightforward."
"Offers a tremendous amount of flexibility and scalability when integrating with applications."
"It provides good access capabilities to various platforms."
"The product is pretty resilient."
"Azure Search is well-documented, making it easy to understand and implement."
"The customer engagement was good."
 

Cons

"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."
"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."
"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."
"You have to build out the metadata yourself because of the nature of the cloud."
"The solution should include a better API for query services."
"The pricing is room for improvement."
"Adding items to Azure Search using its .NET APIs sometimes throws exceptions."
"It would be good if the site found a better way to filter things based on subscription."
"For SDKs, Azure Search currently offers solutions for .NET and Python. Additional platforms would be welcomed, especially native iOS and Android solutions for mobile development."
"For availability, expanding its use to all Azure datacenters would be helpful in increasing awareness and usage of the product.​"
"The initial setup is not as easy as it should be."
"The solution's stability could be better."
"The after-hour services are slow."
 

Pricing and Cost Advice

"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."
"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."
"For the actual costs, I encourage users to view the pricing page on the Azure site for details.​"
"I would rate the pricing an eight out of ten, where one is the low price, and ten is the high price."
"​When telling people about the product, I always encourage them to set up a new service using the free pricing tier. This allows them to learn about the product and its capabilities in a risk-free environment. Depending on their needs, the free tier may be suitable for their projects, however enterprise applications will most likely required a higher, paid tier."
"I think the solution's pricing is ok compared to other cloud devices."
"The solution is affordable."
"The cost is comparable."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Computer Software Company
14%
Manufacturing Company
11%
Healthcare Company
8%
Computer Software Company
20%
Financial Services Firm
12%
Retailer
8%
Manufacturing Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise3
Large Enterprise2
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise2
Large Enterprise4
 

Questions from the Community

What needs improvement with Amazon Athena?
I don't have any specific answer on how Amazon Athena can be improved. This integration is more on the Glue side rather than on Amazon Athena, I would guess. Nothing comes to my mind here. In terms...
What is your primary use case for Amazon Athena?
The typical use case for Amazon Athena is that we have data in a data lake, and if we need to query the data from the data lake, we use Amazon Athena before it gets to the data warehouse where we w...
What advice do you have for others considering Amazon Athena?
I have experience of integration of Amazon Athena with AWS Glue. I think the pricing of Amazon Athena is quite reasonable as we use it in pay-as-you-go mode. On a scale from one to ten, I rate Amaz...
What needs improvement with Azure Search?
We used the semantic search capabilities of Azure AI Search, but we haven't gotten good results in the semantic search. So we are exploring with ChromaDB, and Cosmos is having the capability of doi...
What is your primary use case for Azure Search?
Our use case for Azure AI Search is that we earlier thought to build a vector search and used to have the vector search query in Azure AI Search. Earlier, when it was a search service, we used to l...
What advice do you have for others considering Azure Search?
I can answer a few questions about Azure AI Search to share my opinion. I am still working with Azure and using Azure solutions. We haven't used Cognitive Skills in Azure AI Search. We also got a d...
 

Overview

 

Sample Customers

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday
XOMNI, Real Madrid C.F., Weichert Realtors, JLL, NAV CANADA, Medihoo, autoTrader Corporation, Gjirafa
Find out what your peers are saying about Amazon Athena vs. Azure AI Search and other solutions. Updated: December 2025.
880,844 professionals have used our research since 2012.