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Amazon OpenSearch Service vs Datadog comparison

 

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
22nd
Ranking in Log Management
18th
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
13
Ranking in other categories
Search as a Service (3rd)
Datadog
Ranking in Application Performance Monitoring (APM) and Observability
1st
Ranking in Log Management
4th
Average Rating
8.6
Reviews Sentiment
7.0
Number of Reviews
210
Ranking in other categories
Network Monitoring Software (4th), IT Infrastructure Monitoring (2nd), Container Monitoring (3rd), Cloud Monitoring Software (1st), AIOps (1st), Cloud Security Posture Management (CSPM) (5th), AI Observability (1st)
 

Mindshare comparison

As of May 2026, in the Application Performance Monitoring (APM) and Observability category, the mindshare of Amazon OpenSearch Service is 1.1%, down from 1.9% compared to the previous year. The mindshare of Datadog is 4.7%, down from 9.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Application Performance Monitoring (APM) and Observability Mindshare Distribution
ProductMindshare (%)
Datadog4.7%
Amazon OpenSearch Service1.1%
Other94.2%
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.
Dhroov Patel - PeerSpot reviewer
Site Reliability Engineer at Grainger
Has improved incident response with better root cause visibility and supports flexible on-call scheduling
Datadog needs to introduce more hard limits to cost. If we see a huge log spike, administrators should have more control over what happens to save costs. If a service starts logging extensively, I want the ability to automatically direct that log into the cheapest log bucket. This should be the case with many offerings. If we're seeing too much APM, we need to be aware of it and able to stop it rather than having administrators reach out to specific teams. Datadog has become significantly slower over the last year. They could improve performance at the risk of slowing down feature work. More resources need to go into Fleet Automation because we face many problems with things such as the Ansible role to install Datadog in non-containerized hosts. We mainly want to see performance improvements, less time spent looking at costs, the ability to trust that costs will stay reasonable, and an easier way to manage our agents. It is such a powerful tool with much potential on the horizon, but cost control, performance, and agent management need improvement. The main issues are with the administrative side rather than the actual application.

Quotes from Members

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

Pros

"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"
"In case there is a failure, Elastic manages everything well, and there no major downtime."
"Amazon OpenSearch Service provides a managed database solution, so we don't need to manage everything ourselves."
"Amazon OpenSearch Service has enhanced our organization's ability to store and search large amounts of data efficiently."
"AWS has now made our life easy."
"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."
"They have the good documentation in the help text and that is the reason the Amazon Elasticsearch is the perfect solution for the current market."
"The customer service is excellent, rated nine out of ten."
"Its integration is most valuable because you can integrate it with various service providers such as AWS, .Net, etc."
"Across CCM and the rest of Datadog, I like how sharable everything is."
"Session recordings have been the most valuable to me as it helps me gain insights into user behaviour at scale."
"Real user monitoring gives us invaluable insights into actual user experiences, helping us prioritize improvements where they matter most."
"With Datadog, we managed to get everyone on board into a single place and a single tool, providing teams with one spot where they can check everything related to monitoring, and enabling management and leadership to have an overview of all tools working together."
"I have found error reporting and log centralization the most valuable features. Overall, Datadog provides a full package solution."
"The ingestion points are unlimited and support customization. We haven't had anything yet that we haven't been able to integrate with it."
"We find they have a very helpful alert system."
 

Cons

"As a user, lower prices or reasonable pricing is always better."
"The price is fair yet leans towards the expensive side. I'd rate it five out of ten with respect to capabilities vs. cost."
"One improvement I would like to see is support for auto-scaling."
"They can enhance data visualization."
"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."
"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 configuration should be more straightforward because we had to select a lot of things."
"One improvement I would like to see is support for auto-scaling."
"Another issue that I have is with the search syntax, it could be simpler and it feels like there are too many ways to do the same things."
"More granular control over dashboard sharing. Timeboard sharing."
"We have recently had a number of issues with stability and delays on logging, monitoring, metric evaluation, and alerts."
"There are so many different solutions; it is sometimes difficult to gauge where to start, and I sometimes miss a lot of functionality."
"One thing to improve would be making it easier to see common patterns across traces."
"Datadog is so feature-rich that it is often hard to onboard new folks and tough to decide where to invest time."
"The pricing model hurts and forces us to work around the tool sometimes."
"I found the documentation can sometimes be confusing."
 

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."
"Compared to other cloud platforms, it is manageable and not very expensive."
"The solution is not expensive, but priced averagely, I will say."
"The solution's pricing depends on project volume."
"Our licensing fees are paid on a monthly basis."
"Pricing seemed easy until the bill came in and some things were not accounted for."
"The price is better than some competing products."
"Datadog does not provide any free plans to use the solution. When I start with a proof of concept it would be sensible to have a free plan to test the tool and check whether it fits the requirements of the project. Before the production stage, it is always good to have a free plan with some limited features, number of requests, or logs."
"While it is an expensive product, I would rate the pricing level at four out of five."
"​Pricing seems reasonable. It depends on the size of your organization, the size of your infrastructure, and what portion of your overall business costs go toward infrastructure."
"The price of Datadog is reasonable. Other solutions are more expensive, such as AppDynamics."
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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
15%
Computer Software Company
9%
Manufacturing Company
8%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business7
Midsize Enterprise2
Large Enterprise3
By reviewers
Company SizeCount
Small Business82
Midsize Enterprise47
Large Enterprise100
 

Questions from the Community

What do you like most about Amazon OpenSearch Service?
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
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...
Any advice about APM solutions?
There are many factors and we know little about your requirements (size of org, technology stack, management systems, the scope of implementation). Our goal was to consolidate APM and infra monitor...
Datadog vs ELK: which one is good in terms of performance, cost and efficiency?
With Datadog, we have near-live visibility across our entire platform. We have seen APM metrics impacted several times lately using the dashboards we have created with Datadog; they are very good c...
Which would you choose - Datadog or Dynatrace?
Our organization ran comparison tests to determine whether the Datadog or Dynatrace network monitoring software was the better fit for us. We decided to go with Dynatrace. Dynatrace offers network ...
 

Also Known As

Amazon Elasticsearch Service
No data available
 

Overview

 

Sample Customers

VIDCOIN, Wyng, Yellow New Zealand, zipMoney, Cimri, Siemens, Unbabel
Adobe, Samsung, facebook, HP Cloud Services, Electronic Arts, salesforce, Stanford University, CiTRIX, Chef, zendesk, Hearst Magazines, Spotify, mercardo libre, Slashdot, Ziff Davis, PBS, MLS, The Motley Fool, Politico, Barneby's
Find out what your peers are saying about Amazon OpenSearch Service vs. Datadog and other solutions. Updated: April 2026.
892,943 professionals have used our research since 2012.