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Amazon OpenSearch Service vs Elastic Observability comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Feb 22, 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 Application Performance Monitoring (APM) and Observability
21st
Ranking in Log Management
15th
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
13
Ranking in other categories
Search as a Service (3rd)
Elastic Observability
Ranking in Application Performance Monitoring (APM) and Observability
10th
Ranking in Log Management
14th
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
29
Ranking in other categories
IT Infrastructure Monitoring (13th), Container Monitoring (6th), Cloud Monitoring Software (11th)
 

Mindshare comparison

As of September 2026, in the Application Performance Monitoring (APM) and Observability category, the mindshare of Amazon OpenSearch Service is 0.9%, down from 2.0% compared to the previous year. The mindshare of Elastic Observability is 1.6%, down from 4.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Application Performance Monitoring (APM) and Observability Mindshare Distribution
ProductMindshare (%)
Elastic Observability1.6%
Amazon OpenSearch Service0.9%
Other97.5%
Application Performance Monitoring (APM) and Observability
 

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.
Stefan Decuypere - PeerSpot reviewer
Technology Consultant at Hybrid software
Real-time dashboards and visual insights have streamlined issue analysis and monitoring
After careful consideration about areas for improvement in Elastic Observability, aspects such as pricing, customization, implementation, and scalability could be improved. As a user of the system, I know what it costs but am not directly involved in cost-benefit evaluations or maintenance, which is handled by another team. I develop the visual representation of the data and frankly, I don't see major gaps in my application or anything I would really miss; I appreciate the fast pace of the developments that have occurred in the last couple of years. Regarding room for improvement in Elastic Observability, I would have preferred built-in tools to manage the indexes on deployment for better visual representation, as the initial feedback regarding system performance and data storage was fairly primitive and lacking.

Quotes from Members

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

Pros

"The business analytics capabilities are the most important feature it provides."
"It's actually easier to collaborate since it is already deployed in the AWS cloud itself."
"It's a good log management platform. In terms of infrastructure management, it's good."
"We retrieve historical data with just a click of a button to move it from cold to hot or warm because it's already stored in the backend storage"
"The initial set up is very easy...We really appreciate Amazon!"
"The most valuable features of Amazon Elasticsearch are ease of use, native JSON, and efficiency. Additionally, handles many use cases and search grammar was useful."
"Amazon OpenSearch Service provides a managed database solution, so we don't need to manage everything ourselves."
"Regarding valuable features of the solution, we found with the process, which we have used in both cases where we used the solution that while you're seeing the streaming of data, you can analyze in the initial phase what sort of data you are streaming and whether it is valuable."
"Elastic APM has plenty of features, such as the Elastic server for Kibana and many additional plugins. It's a comprehensive tool when used as a logging platform."
"Elastic Observability is highly stable; we ingested nearly 170 million records in the system and we have tested it, and you get your reports and dashboards within a few seconds, so it doesn't take much time."
"Elastic Observability significantly improves incident response time by providing quick access to logs and data across various sources. For instance, searching for specific keywords in logs spanning over a month from multiple data sources can be completed within seconds."
"The product has connectors to many services."
"The solution has been stable in our usage."
"It is scalable and supports multitenancy, which is beneficial for MSPs."
"For full stack observability, Elastic is the best tool compared with any other tool like New Relic or AppDynamics or Dynatrace."
"The solution allows us to track performance via metrics and we're able to see where latency is happening."
 

Cons

"We faced documentation challenges during integration after migrating from Elasticsearch to Amazon OpenSearch Service. Better documentation on integration, query handling, and a more user-friendly UI could enhance the product."
"They can enhance data visualization."
"As a user, lower prices or reasonable pricing is always better."
"I want to see a new feature in Amazon Elasticsearch Service that allows users to create default filters for filtered levels."
"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."
"The price is fair yet leans towards the expensive side. I'd rate it five out of ten with respect to capabilities vs. cost."
"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."
"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."
"Elastic Observability could improve asset discovery as the current requirement to push the agent is not ideal."
"There's a steep learning curve if you've never used this solution before."
"There is room for improvement regarding its APM capabilities."
"The tool's scalability involves a more complex implementation process. It requires careful calculations to determine the number of nodes needed, the specifications of each node, and the configuration of hot, warm, and cold zones for data storage. Additionally, managing log retention policies adds further complexity. The solution's pricing also needs to be cheaper."
"If we had some pre-defined templates for observability that we could start using right away after deploying it – instead of having to build or to change some of the dashboards – that would be helpful."
"Elastic Observability is an excellent product for monitoring and visibility, but it lacks predictive analytics. Most solutions are aligned with the AIOps requirements, but this piece is missing in Elastic and should be included."
"The price is the only issue in the solution. It can be made better and cheaper."
"Elastic Observability needs to have better standardization, logging, and schema."
 

Pricing and Cost Advice

"You only pay for what you use."
"There is a community edition available and the price of the commercial offering is reasonable."
"The solution is not expensive, but priced averagely, I will say."
"Compared to other cloud platforms, it is manageable and not very expensive."
"Elastic Observability is cheaper than other similar solutions, such as Dynatrace. Its license calculation is based on various factors like data volume and physical infrastructure, particularly related to RAM capacity."
"Pricing is one of those situations where the more you use it, the more you pay."
"The price of Elastic Observability is expensive."
"The product is not that cheap."
"The product’s pricing needs improvement."
"Elastic Observability's pricing could be better for small-scale users."
"Users have to pay for some features, like the alerts on different channels, because they are unavailable in different source versions."
"There are two types: cloud and SaaS. They charge based on data ingestion, ingest rate, hard retention, and warm retention. I believe it costs around $25,000 annually to ingest 30GB of data daily. That is the SaaS version. There is also a self-managed license where the customer manages their own infrastructure on-prem. In such cases, there are three license tiers that respectively cost $5,000 annually per node, $7,000 per node, and $12,500 per node."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Manufacturing Company
10%
Computer Software Company
8%
Outsourcing Company
6%
Financial Services Firm
14%
Computer Software Company
9%
Comms Service Provider
7%
Manufacturing Company
7%
 

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 Business9
Midsize Enterprise4
Large Enterprise16
 

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 Elastic Observability?
The problem is their licensing model, which is a bit confusing. Many customers struggle to understand their total cost of ownership because Elastic licensing is not dependent on easy, quantifiable ...
What needs improvement with Elastic Observability?
After careful consideration about areas for improvement in Elastic Observability, aspects such as pricing, customization, implementation, and scalability could be improved. As a user of the system,...
What is your primary use case for Elastic Observability?
My use case for Elastic Observability is observability, as we upload our customers' data, including logs, and when there is an issue, we can analyze what went wrong.
 

Also Known As

Amazon Elasticsearch Service
No data available
 

Overview

 

Sample Customers

VIDCOIN, Wyng, Yellow New Zealand, zipMoney, Cimri, Siemens, Unbabel
PSCU, Entel, VITAS, Mimecast, Barrett Steel, Butterfield Bank
Find out what your peers are saying about Amazon OpenSearch Service vs. Elastic Observability and other solutions. Updated: September 2026.
913,806 professionals have used our research since 2012.