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Amazon OpenSearch Service vs Prometheus-AI Platform comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Mar 29, 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
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 (18th), Search as a Service (3rd)
Prometheus-AI Platform
Average Rating
8.2
Reviews Sentiment
6.9
Number of Reviews
34
Ranking in other categories
Data Scrubbing Software (6th), ERP (26th), Enterprise Asset Management (EAM) (7th)
 

Mindshare comparison

Amazon OpenSearch Service and Prometheus-AI Platform aren’t in the same category and serve different purposes. Amazon OpenSearch Service is designed for Application Performance Monitoring (APM) and Observability and holds a mindshare of 1.1%, down 1.9% compared to last year.
Prometheus-AI Platform, on the other hand, focuses on Enterprise Asset Management (EAM), holds 1.6% mindshare.
Application Performance Monitoring (APM) and Observability Mindshare Distribution
ProductMindshare (%)
Amazon OpenSearch Service1.1%
Dynatrace5.5%
Datadog4.7%
Other88.7%
Application Performance Monitoring (APM) and Observability
Enterprise Asset Management (EAM) Mindshare Distribution
ProductMindshare (%)
Prometheus-AI Platform1.6%
IBM Maximo13.1%
Oracle Enterprise Asset Management7.3%
Other78.0%
Enterprise Asset Management (EAM)
 

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.
MuhammadAzhar Khan - PeerSpot reviewer
Senior DevOps Engineer at Alibaba Group
Free to use and provides valuable monitoring capabilities
Prometheus is a scalable and flexible tool that I can deploy on any cloud platform. It is free to use and provides valuable monitoring capabilities. It allows me to save money by avoiding costs associated with AWS native services like CloudWatch or Amazon Prometheus. The ability to deploy on any cloud platform or environment, including Kubernetes, is a major advantage.

Quotes from Members

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

Pros

"The stability of the product is good."
"It's actually easier to collaborate since it is already deployed in the AWS cloud itself."
"AWS has now made our life easy."
"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"
"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."
"It's a good log management platform. In terms of infrastructure management, it's good."
"The customer service is excellent, rated nine out of ten."
"The business analytics capabilities are the most important feature it provides."
"The most valuable features of the solution are metrics scraping capabilities and the open source community and support."
"It has lots of APIs and libraries to integrate with any kind of language."
"It has lots of APIs and libraries to integrate with any kind of language, including Python, Perl, PHP, Java, and Kotlin."
"The most valuable feature of Prometheus is its ability to collect metrics."
"It is a scalable solution."
"The product has an easy-to-understand interface."
"Prometheus gives us high availability automatically."
"Prometheus is a scalable and flexible tool that I can deploy on any cloud platform."
 

Cons

"The configuration should be more straightforward because we had to select a lot of things."
"The price is fair yet leans towards the expensive side. I'd rate it five out of ten with respect to capabilities vs. cost."
"The pricing aspect is a concern. The service is way too costly. For the past month, I used only 30 to 40 MB of data, and the cost was $500. AWS could improve pricing."
"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."
"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."
"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."
"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."
"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."
"When it comes to deployment, if you have no experience with something like a CI/CD pipeline, it might be a challenge."
"The alert functionality is kind of lackluster."
"The solution has shortcomings regarding security monitoring-oriented features to support custom use cases, like out-of-the-box test scenarios and threat-related use cases of its users."
"The product must improve its documentation."
"There is a need for a more comprehensive overview of exporters, especially when dealing with many of them."
"Lacks the ability to clusterize."
"The simplicity of the query language could be improved. The current query language is not easy to work with."
"They could provide efficient logs in terms of clarity and ease of access similar to Datadog’s paid version."
 

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."
"The solution is free of cost."
"Prometheus is available as an open-source product."
"This is an open-source solution."
"Prometheus is an open-source tool."
"My company uses the open-source version of the product."
"We use the solution's open-source version."
"The solution is open source."
"The solution is not expensive."
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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
18%
Computer Software Company
10%
Manufacturing Company
7%
Comms Service Provider
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 Business14
Midsize Enterprise8
Large Enterprise12
 

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...
What is your experience regarding pricing and costs for Prometheus?
Prometheus is cost-effective for me as it is free. Using cloud-native alternatives like Amazon Prometheus would incur charges.
What is your primary use case for Prometheus?
I use Prometheus for monitoring purposes in IT infrastructure. It is particularly useful for environments using Kubernetes, as it monitors ports, containers, instances, and applications effectively.
What advice do you have for others considering Prometheus?
As a new user, I should be familiar with syntax and commands. Online resources like Google and ChatGPT can be helpful. I should consider using cloud-native tools for ease of management if not using...
 

Also Known As

Amazon Elasticsearch Service
Utopia Data Quality
 

Overview

 

Sample Customers

VIDCOIN, Wyng, Yellow New Zealand, zipMoney, Cimri, Siemens, Unbabel
Harley-Davidson Motor Company, Roche Diagnostics Corporation, Harman International Industries Inc., Hilmar Cheese Company, International Rectifier Corporation, Electrolux USA, GE Fanuc Intelligent Platforms, Rio Tinto Limited, Pertamina Pusat, Petrofac International Ltd, Cintas Corporation, Diyar United Company, Nortel Networks, Verizon
Find out what your peers are saying about Amazon OpenSearch Service vs. Prometheus-AI Platform and other solutions. Updated: September 2025.
893,244 professionals have used our research since 2012.