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Amazon Kendra vs Elastic 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 Kendra
Ranking in Search as a Service
2nd
Average Rating
7.6
Reviews Sentiment
7.1
Number of Reviews
2
Ranking in other categories
No ranking in other categories
Elastic Search
Ranking in Search as a Service
1st
Average Rating
8.2
Reviews Sentiment
6.7
Number of Reviews
67
Ranking in other categories
Indexing and Search (1st), Cloud Data Integration (10th), Vector Databases (2nd)
 

Mindshare comparison

As of April 2025, in the Search as a Service category, the mindshare of Amazon Kendra is 16.6%, down from 22.0% compared to the previous year. The mindshare of Elastic Search is 14.4%, up from 8.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Search as a Service
 

Featured Reviews

AM
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.
Anand_Kumar - PeerSpot reviewer
Captures data from all other sources and becomes a MOM aka monitoring of monitors
Scalability and ROI are the areas they have to improve. Their license terms are based on the number of cores. If you increase the number of cores, it becomes very difficult to manage at a large scale. For example, if I have a $3 million project, I won't sell it because if we're dealing with a 10 TB or 50 TB system, there are a lot of systems and applications to monitor, and I have to make an MOM (Mean of Max) for everything. This is because of the cost impact. Also, when you have horizontal scaling, it's like a multi-story building with only one elevator. You have to run around, and it's not efficient. Even the smallest task becomes difficult. That's the problem with horizontal scaling. They need to improve this because if they increase the cores and adjust the licensing accordingly, it would make more sense.

Quotes from Members

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

Pros

"Provides flexibility to tune the relevance and ranking of results."
"We have good use cases where stability is everything. So it's a stable solution."
"I find the solution to be fast."
"Data indexing of historical data is the most beneficial feature of the product."
"It is highly valuable because of its simplicity in maintenance, where most tasks are handled for you, and it offers a plethora of built-in features."
"The most valuable features are the detection and correlation features."
"It is a stable and good platform."
"The AI-based attribute tagging is a valuable feature."
"The flexibility and the support for diverse languages that it provides for searching the database are most valuable. We can use different languages to query the database."
"There's lots of processing power. You can actually just add machines to get more performance if you need to. It's pretty flexible and very easy to add another log. It's not like 'oh, no, it's going to be so much extra data'. That's not a problem for the machine. It can handle it."
 

Cons

"There are some token limits."
"The time it takes for indexing documents could be reduced."
"There should be more stability."
"I have not been using the solution for many years to know exactly the improvements needed. However, they could simplify how the YML files have to be structured properly."
"Elastic Search should provide better guides for developers."
"The solution's integration and configuration are not easy. Not many people know exactly what to do."
"Elastic Enterprise Search can improve by adding some kind of search that can be used out of the box without too much struggle with configuration. With every kind of search engine, there is some kind of special function that you need to do. A simple out-of-the-box search would be useful."
"We see the need for some improvements with Elasticsearch. We would like the Elasticsearch package to include training lessons for our staff."
"Elastic Enterprise Search could improve its SSL integration easier. We should not need to go to the back-end servers to do configuration, we should be able to do it on the GUI."
"While integrating with tools like agents for ingesting data from sources like firewalls is valuable, I believe prioritizing improvements to the core product would be more beneficial."
 

Pricing and Cost Advice

"The pricing falls in the medium range."
"The solution is less expensive than Stackdriver and Grafana."
"The solution is affordable."
"The premium license is expensive."
"An X-Pack license is more affordable than Splunk."
"​The pricing and license model are clear: node-based model."
"Although the ELK Elasticsearch software is open-source, we buy the hardware."
"The solution is free."
"The version of Elastic Enterprise Search I am using is open source which is free. The pricing model should improve for the enterprise version because it is very expensive."
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Top Industries

By visitors reading reviews
Computer Software Company
20%
Financial Services Firm
18%
Manufacturing Company
10%
Retailer
6%
Computer Software Company
18%
Financial Services Firm
15%
Government
9%
Manufacturing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Amazon Kendra?
We have good use cases where stability is everything. So it's a stable solution.
What is your experience regarding pricing and costs for Amazon Kendra?
The pricing falls in the medium range. The cost depends on the size of your use case because it has a fixed cost, not a variable. The licensing is on a monthly basis. There are no extra costs. Only...
What needs improvement with Amazon Kendra?
There are some token limits. We cannot ask questions with more than 30 tokens. Access cannot be more than 200 tokens. And the token is also, like, one point. Then views are very hard limits, and it...
What do you like most about ELK Elasticsearch?
Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time anal...
What is your experience regarding pricing and costs for ELK Elasticsearch?
I don't know about pricing. That is dealt with by the sales team and our account team. I was not involved with that.
What needs improvement with ELK Elasticsearch?
I found an issue with Elasticsearch in terms of aggregation. They are good, yet the rules written for this are not really good. There is a maximum of 10,000 entries, so the limitation means that if...
 

Comparisons

 

Also Known As

No data available
Elastic Enterprise Search, Swiftype, Elastic Cloud
 

Overview

 

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
T-Mobile, Adobe, Booking.com, BMW, Telegraph Media Group, Cisco, Karbon, Deezer, NORBr, Labelbox, Fingerprint, Relativity, NHS Hospital, Met Office, Proximus, Go1, Mentat, Bluestone Analytics, Humanz, Hutch, Auchan, Sitecore, Linklaters, Socren, Infotrack, Pfizer, Engadget, Airbus, Grab, Vimeo, Ticketmaster, Asana, Twilio, Blizzard, Comcast, RWE and many others.
Find out what your peers are saying about Amazon Kendra vs. Elastic Search and other solutions. Updated: March 2025.
842,690 professionals have used our research since 2012.