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Amazon OpenSearch Service vs Elastic Search comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jun 3, 2026

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 OpenSearch Service
Ranking in Search as a Service
3rd
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
13
Ranking in other categories
Application Performance Monitoring (APM) and Observability (22nd), Log Management (19th)
Elastic Search
Ranking in Search as a Service
1st
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
99
Ranking in other categories
Indexing and Search (1st), Cloud Data Integration (5th), Vector Databases (5th)
 

Mindshare comparison

As of June 2026, in the Search as a Service category, the mindshare of Amazon OpenSearch Service is 11.5%, up from 7.2% compared to the previous year. The mindshare of Elastic Search is 17.2%, up from 16.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Search as a Service Mindshare Distribution
ProductMindshare (%)
Elastic Search17.2%
Amazon OpenSearch Service11.5%
Other71.3%
Search as a Service
 

Featured Reviews

Md. Shahariar Hossen - PeerSpot reviewer
Senior Software Engineer at Cefalo
Event tracking has become smoother and data analytics provide clear insights for user actions
Amazon OpenSearch Service is not providing the processing feature directly. From Amazon OpenSearch Service, we are actually maintaining the AWS SQS, the queue service, which is responsible for providing information about what data has to be modified. So using that SQS, we're actually providing it, but we're not directly using Amazon OpenSearch Service for keeping data to other data pipeline thing. So far we didn't use it for any machine learning purposes, but in future, we have plans to extend or implement this feature. Since AWS itself is secure and Amazon OpenSearch Service is a part of this entire ecosystem, it becomes much easier for security purposes. From the validation point of view, Amazon OpenSearch Service itself provides easy to communicate APIs and up-to-date documents, which is much beneficial. For example, if I'm missing anything, I can directly go and check the documentation. That is actually much easier. I would rate it as really good so far. It's much faster. For our local machine, we can also use a kind of replica of Amazon OpenSearch Service just for development purposes. That is another good feature. I would say for the encryption thing and also the user access control management, it's much faster. For some of these hashing algorithms, it also worked really well so far. To be honest, I didn't find any places where it can be improved. However, I think they could provide more abstraction. For example, still for searching, we have to write down the queries in a specific manner, such as for a specific JSON structure or in a specific way. Otherwise, they don't provide us the actual results. For at least this purpose, I think abstraction could be a bit easier or a bit improved. Other than that, right now there is the age of AI, so some kind of prompting could also work, but I'm not sure how it could be integrated. As a user, lower prices or reasonable pricing is always better. Those can be improved as well. However, it is good that most of the services including Amazon OpenSearch Service actually provide pay as you go pricing. So if there were a bit lower version or a bit less payment methodology, it might be much better.
reviewer2817942 - PeerSpot reviewer
Senior Software Engineer at a consultancy with 11-50 employees
Logging and vector search have transformed observability and empowered reliable ai agents
Elastic Search is not specifically being used for certain purposes. I deploy Elastic Search database on the cloud and use cloud services so that nobody can attack. However, I do not use Elastic Search to resolve attack issues. The basic main purpose of Elastic Search, as of now, I feel it can do more in the AI area. Sometime I saw that when I am developing RAG and have to generate the embeddings, which I call metadata, sometimes it tries to fail. That durability or issue handling should be improved, but apart from that, I did not find anything as of now. As per my use case, whatever I am using seems pretty good. Apart from that, some definitely improvement will be there. One improvement is that it should be faster. Whenever I am searching any logs, it takes much time. For example, if I open my log in Notepad or a similar tool, I can search the text within a second. With Elastic Search, it takes a little bit of time, ten to fifteen seconds. That can be improved. Sometimes, engineers take time to assign when I create a ticket.

Quotes from Members

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

Pros

"It's actually easier to collaborate since it is already deployed in the AWS cloud itself."
"In case there is a failure, Elastic manages everything well, and there no major downtime."
"The stability of the product is good."
"This service already sorts data like vectors. They have classified the storage pre-defined."
"It's a good log management platform. In terms of infrastructure management, it's good."
"Amazon OpenSearch Service provides a managed database solution, so we don't need to manage everything ourselves."
"The customer service is excellent, rated nine out of ten."
"It enables us to efficiently search and retrieve our event data, offering us a versatile approach to locate specific information within these logs."
"From a technical point of view, there are no significant issues recalled as Elastic Search has been absolutely awesome for this use case and covers 100% of the needs."
"The forced merge and forced resonate features reduce the data size increasing reliability."
"A good use case is saving metadata of your systems for data cataloging. Various systems, like those opened in metadata and similar applications, use Elasticsearch to store their text data."
"Elastic is doing a fantastic job by doing the indexing, and with a couple of indexing configurations, we are able to achieve our goal even though we are maintaining a huge amount of data per day, around millions of transactions for each record."
"We are developing a SIEM application that is similar to QRadar, ArcSight, or Splunk, and this application uses Elasticsearch as its search engine because we want to retrieve information fast."
"The most valuable feature of the solution is its utility and usefulness."
"You have dashboards, it is visual, there are maps, you can create canvases. It's more visual than anything that I've ever used."
"The product offers a powerful, cost effective solution for proprietary log management and is easy to understand and start with."
 

Cons

"One glaring issue was with our mapping configuration as the system accepted the data we posted, but after a few months, when we attempted complex queries, we realized the date formatting had become problematic."
"One improvement I would like to see is support for auto-scaling."
"I would say that, basically, the configuration part is an area with a shortcoming...Some upgradation is required on the configuration side so that we can get to use it."
"In terms of data handling capabilities with Amazon OpenSearch Service, they can be complex and managing data in comparison to other SIM solutions is a major drawback, as it is very hard to handle the data."
"There is the problem with the database. Amazon only provides the host to run to our applications bias, but there is no option to manage the database within the Elasticsearch product."
"I want to see a new feature in Amazon Elasticsearch Service that allows users to create default filters for filtered levels."
"Amazon Elasticsearch can improve the bullion in the near search and the ease of integration with Kibana. Additionally, there could be more flexibility in the configuration and documentation."
"The price is fair yet leans towards the expensive side. I'd rate it five out of ten with respect to capabilities vs. cost."
"Pagination in Elastic Search is very slow."
"Regarding what I dislike about Elastic Search, there is one issue that occurs because Elastic Search is not my primary database; it serves as a substitute database for the searching part."
"Elasticsearch could be improved in terms of scalability."
"The solution must provide AI integrations."
"I found an issue with Elasticsearch in terms of aggregation. They are good, yet the rules written for this are not really good."
"I found an issue with Elasticsearch in terms of aggregation. There is a maximum of 10,000 entries, so the limitation means that if I wanted to analyze certain IP addresses more than 10,000 times, I wouldn't be able to dump or print that information."
"I think the first area for improvement is pricing, as the cluster cost for Elastic Search is too high for me."
"I think Elastic Search could be improved by introducing more AI features, particularly for complex queries and aggregator functions to enhance usability and readability."
 

Pricing and Cost Advice

"The solution is not expensive, but priced averagely, I will say."
"Compared to other cloud platforms, it is manageable and not very expensive."
"You only pay for what you use."
"There is a community edition available and the price of the commercial offering is reasonable."
"The tool is not expensive. Its licensing costs are yearly."
"It can be expensive."
"The solution is affordable."
"The price could be better."
"ELK has been considered as an alternative to Splunk to reduce licensing costs."
"We use the free version for some logs, but not extensive use."
"The pricing model is questionable and needs to be addressed because when you would like to have the security they charge per machine."
"The pricing structure depends on the scalability steps."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Manufacturing Company
10%
Computer Software Company
10%
Government
6%
Financial Services Firm
13%
Manufacturing Company
9%
Computer Software Company
8%
Retailer
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business7
Midsize Enterprise2
Large Enterprise4
By reviewers
Company SizeCount
Small Business40
Midsize Enterprise12
Large Enterprise49
 

Questions from the Community

What is your experience regarding pricing and costs for Amazon OpenSearch Service?
I would consider the pricing as a six based on how much data we are handling; if we handle minimal data, it's cheap, but for large data, it becomes costly. Our clients usually pay between $1,000 to...
What needs improvement with Amazon OpenSearch Service?
Amazon OpenSearch Service is not providing the processing feature directly. From Amazon OpenSearch Service, we are actually maintaining the AWS SQS, the queue service, which is responsible for prov...
What is your primary use case for Amazon OpenSearch Service?
Amazon OpenSearch Service is a user-friendly version of Elasticsearch, as per my understanding. I have been using it for our volunteer management system where around 5,000 to 6,000 users are using ...
What is your experience regarding pricing and costs for ELK Elasticsearch?
Elastic Search is easy to use in Azure cloud. Mostly, my full company uses Azure cloud, so it is easy to use. Cost-wise, my company found Elastic Search is good. Cost matters. Based on cost and use...
What needs improvement with ELK Elasticsearch?
The initial configuration could be easier; at first, the learning curve is a little high, and over time, it becomes easier. For me, the initial configuration might be improved.
What is your primary use case for ELK Elasticsearch?
We use Elastic Search for a research application based on paper study, and the primary usage is for indexing the data and then functioning in a similar way to an e-commerce search bar.
 

Also Known As

Amazon Elasticsearch Service
Elastic Enterprise Search, Swiftype, Elastic Cloud
 

Overview

 

Sample Customers

VIDCOIN, Wyng, Yellow New Zealand, zipMoney, Cimri, Siemens, Unbabel
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 OpenSearch Service vs. Elastic Search and other solutions. Updated: June 2026.
900,747 professionals have used our research since 2012.