Amazon OpenSearch Service vs Elastic Stack comparison

Amazon Web Services (AWS) and Elastic are both solutions in the Log Management category. Amazon Web Services (AWS) is ranked #19 with an average rating of 7.3, while Elastic is ranked #11 with an average rating of 7.7. Amazon Web Services (AWS) holds a 2.2% mindshare in Log Management, compared to Elastic’s 3.5% mindshare. Additionally, 92% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Elastic users who would recommend it.

Amazon OpenSearch Service

Read 13 Amazon OpenSearch Service reviews

5,362 Views
3,056 Comparison Views

92% willing to recommend

Elastic Stack

Read 18 Elastic Stack reviews

5,825 Views
5,825 Comparison Views

100% willing to recommend

Amazon OpenSearch Service

Elastic Stack

Comparison Buyer's Guide

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Executive SummaryUpdated on Nov 16, 2025

Elastic Stack and Amazon OpenSearch Service are both strong contenders in the search and analytics domain. Overall, Amazon OpenSearch Service appears to have the upper hand due to its extensive features and support.

Features: Elastic Stack's open-source nature allows for customizable components. It shines with its real-time data visualization and robust search engine capabilities. Amazon OpenSearch Service, on the other hand, offers seamless AWS integration, managed infrastructure, and scalable features that enhance versatility.

Room for Improvement: Elastic Stack may require advanced technical expertise and structured support channels to improve user experience. It could also benefit from additional automated scaling solutions. Amazon OpenSearch Service can enhance its flexibility outside the AWS ecosystem. Better community-driven options and increased support for diverse infrastructure could be advantageous.

Ease of Deployment and Customer Service: Elastic Stack demands a more hands-on setup, providing flexibility but also requiring a high level of technical knowledge. Amazon OpenSearch Service benefits from the convenience of AWS's managed support, which includes automatic updates, backups, and comprehensive support channels.

Pricing and ROI: Elastic Stack offers initial cost benefits due to its open-source foundation, though management and scaling can add unforeseen expenses. Despite higher initial costs, Amazon OpenSearch Service provides better long-term ROI through reduced operational overhead and efficiency-enhancing features.

To learn more, read our detailed Amazon OpenSearch Service vs. Elastic Stack Report (Updated: December 2025).

Buyer's Guide

Amazon OpenSearch Service vs. Elastic Stack

December 2025

Download the complete report

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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 Log Management

19th

Average Rating

7.6

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Application Performance Monitoring (APM) and Observability (23rd), Search as a Service (3rd)

Elastic Stack

Ranking in Log Management

11th

Average Rating

8.0

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of February 2026, in the Log Management category, the mindshare of Amazon OpenSearch Service is 2.2%, up from 1.8% compared to the previous year. The mindshare of Elastic Stack is 3.5%, down from 4.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Log Management Market Share Distribution
Product	Market Share (%)
Elastic Stack	3.5%
Amazon OpenSearch Service	2.2%
Other	94.3%

Log Management

Featured Reviews

Md. Shahariar Hossen

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.

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Lakshmi Bodepu

Senior Consultant at Skillfield

Offers robust out-of-the-box integrations and streamlines logging processes effortlessly

There are improvements needed for Elastic Stack. It is mostly based on Lucene, and the heart of Elastic Stack is Lucene, which has some limitations. Anything built on top of Lucene often feels an add-on, and that includes vector databases. Elastic Stack can store vector embeddings as well and perform AI and machine learning tasks out of the box without excessive configuration. The main improvements involve increasing speed and compression capabilities; I have seen databases that claim to achieve significantly better compression. While Elastic Stack can manage vast amounts of data, if the mapping is not specified correctly, the indexing time can be slow, especially with many events per second. Improper mapping usually means that every document received gets indexed for all fields, which is not desired. Elastic consultants typically optimize this, but out of the box, as data volume increases, scaling becomes necessary. They are working on these improvements in new versions.

Read full review

Quotes from Members

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

Pros

"Amazon OpenSearch Service provides a managed database solution, so we don't need to manage everything ourselves."

"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."

"The initial set up is very easy...We really appreciate Amazon!"

"It enables us to efficiently search and retrieve our event data, offering us a versatile approach to locate specific information within these logs."

"This service already sorts data like vectors. They have classified the storage pre-defined."

"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 stability of the product is good."

"The customer service is excellent, rated nine out of ten."

More Amazon OpenSearch Service pros

"The only beneficial aspect of Elastic Stack is that it's open source."

"I have benefited from the security features provided by X-Pack in Elastic Stack, particularly the SIEM capability, which is very good for checking security issues."

"We can group a lot of alarms into one automation alarm supervision. The alarm supervision allows us to put the alarm under the same. It's quite helpful for us. We used that to suppress our alarms. Elastic already provides the agent. It is easy to integrate Elastic Stack with other devices and vendors."

"I think the ecosystem is well supported, and for logs, it was faster compared to our previous previous log management."

"The tool is huge, and it performs brilliantly. I tested it for malware, and within two weeks of launching, the product alerted me about a network intrusion. This was a tough test for it, but it performed admirably. The alerting system is excellent, and searching through logs is incredibly efficient. What's impressive is that all three products or options are integrated into one solution. This means I don't need separate logging, monitoring, or antivirus solutions."

"The solution's technical support is good...Elastic Stack offers good value for value for money based on the product's features and what they offer."

"It is a very scalable solution...I didn't face any problem with this scalability part of the solution since we only have a few pieces of equipment in our company."

"The machine learning capabilities are valuable."

More Elastic Stack pros

Cons

"There is a problem with the database. Amazon only provides the hosting to run our applications bias, but there is no option to manage the database within the Elasticsearch product."

"As a user, lower prices or reasonable pricing is always better."

"One improvement I would like to see is support for auto-scaling."

"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."

"The configuration should be more straightforward because we had to select a lot of things."

"It would be beneficial to have some level of customization available in the managed service, tailored to the specific use cases of the end users."

"I want to see a new feature in Amazon Elasticsearch Service that allows users to create default filters for filtered levels."

"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."

More Amazon OpenSearch Service cons

"It should facilitate easier manual integration."

"It lacks a clear NDR (Network Detection and Response) feature. If Elastic could enhance this aspect, it would significantly boost its capabilities."

"Elastic Stack should be more simplified with ready-to-use widgets."

"Elastic Stack should be more simplified with ready-to-use widgets. Also, incorporating AI capabilities is essential as monitoring and observability tools are now adding AI features."

"The tool's pricing can be improved."

"The main issue related to Elastic Stack is in the area of its licensing."

"Elastic Stack's search capabilities can be challenging, especially when searching for precise data from past years, such as two or ten years ago. Its indexing performance for exact data retrieval may decrease as the data volume grows. Therefore, I believe there is room for improvement in the product's search functionality. It needs to improve its pricing as well."

"The stability of the solution is rated as three or four out of ten as we frequently encounter issues."

More Elastic Stack cons

Pricing and Cost Advice

"The solution is not expensive, but priced averagely, I will say."

"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."

"I used the open-source version of Elastic Stack, because of which I did not have to pay anything."

"The product is expensive."

"I rate the solution's pricing a six out of ten."

"If I compare Elastic Stack to the other products in the market, I would say that the tool is available at a competitive price."

"Ultimately, the pricing depends upon the capacity planning that the enterprise architect does."

"It depends on the specifics, but generally, Elastic is economical for certain use cases."

"We are using the open-source community version of the product."

"The pricing is reasonable."

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Computer Software Company

10%

Manufacturing Company

10%

Government

Computer Software Company

11%

Financial Services Firm

10%

Government

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	7
Midsize Enterprise	2
Large Enterprise	3

By reviewers
Company Size	Count
Small Business	10
Midsize Enterprise	3
Large Enterprise	6

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

See all answers

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...

See all answers

What needs improvement with Amazon OpenSearch Service?

See all answers

What do you like most about Elastic Stack?

The tool is huge, and it performs brilliantly. I tested it for malware, and within two weeks of launching, the product alerted me about a network intrusion. This was a tough test for it, but it per...

See all answers

What is your experience regarding pricing and costs for Elastic Stack?

My experience with Elastic Stack pricing indicates that it is node-based. While I do not have complete pricing details, they are available online. If I choose Elastic Cloud, it includes licensing a...

See all answers

What needs improvement with Elastic Stack?

I would like to improve Elastic Stack by addressing the current big problem we face with importing logs and log files, such as syslogs. To import these log files, we need to design the ingest pipel...

See all answers

Comparisons

Grafana Loki vs Amazon OpenSearch Service

Compared 17% of the time

Datadog vs Amazon OpenSearch Service

Compared 6% of the time

Amazon CloudWatch vs Amazon OpenSearch Service

Compared 6% of the time

Xapien vs Amazon OpenSearch Service

Compared 5% of the time

Amazon Athena vs Amazon OpenSearch Service

Compared 4% of the time

More Amazon OpenSearch Service Competitors

Wazuh vs Elastic Stack

Compared 38% of the time

Security Onion vs Elastic Stack

Compared 12% of the time

Grafana Loki vs Elastic Stack

Compared 6% of the time

Dynatrace vs Elastic Stack

Compared 6% of the time

Splunk Enterprise Security vs Elastic Stack

Compared 1% of the time

More Elastic Stack Competitors

Product Reports

Buyer's Guide

Amazon OpenSearch Service

February 2026

Download Amazon OpenSearch Service product report

Buyer's Guide

Elastic Stack

February 2026

Download Elastic Stack product report

Also Known As

Amazon Elasticsearch Service

No data available

Overview

Amazon OpenSearch Service provides scalable and reliable search capabilities with efficient data processing, supporting easy domain configuration and integration with numerous systems for enhanced performance.

Amazon OpenSearch Service offers advanced features for handling JSON, diverse search grammars, quick historical data retrieval, and ultra-warm storage. It also includes customizable dashboards and seamless tool integration for large enterprises. With its managed infrastructure, OpenSearch Service supports efficient system analysis and business analytics, improving overall performance and flexibility. Despite these features, areas like configuration complexity, lack of auto-scaling, and integration with Kibana require attention. Users seek enhanced documentation, better pricing options, and more flexible data handling. Desired improvements include default filters, mapping configuration, and alerting capabilities. Enhanced data visualization and Compute Optimizer Service integration are also recommended for future updates.

What features define Amazon OpenSearch Service?

Scalable Search: Offers reliable search capabilities across vast datasets.
JSON Handling: Supports efficient management of JSON data.
Ultra-warm Storage: Enables cost-effective historical data retrieval.
Dashboard Customization: Supports tool integration and tailored visuals.
System Upgrades: Allows for seamless infrastructure upgrades.

What benefits and ROI should users consider?

Performance Enhancement: Significant improvement in search and data retrieval.
Cost-Effectiveness: Provides a cloud-native solution optimized for AWS environments.
Comprehensive Analytics: Delivers detailed insights for business applications.

Amazon OpenSearch Service is utilized in various industries for log management, data storage, and search capabilities. It supports infrastructure and embedded management, analyzing logs from AWS Lambda, Kubernetes, and other services. Companies use it for application debugging, monitoring security and performance, and customer behavior analysis, integrating it with tools like DynamoDB and Snowflake for a cost-effective solution.

Amazon Web Services (AWS)

Elastic Stack is a comprehensive tool for log management, observability, indexing, and security, widely adopted for managing logs, alert creation, SIEM, SOC, and threat analysis. It integrates with CloudStrike and Endpoint Security, enhancing search capabilities and Application Performance Monitoring.

Elastic Stack offers powerful solutions for logging, data storage, and visualization with Kibana. It allows MSSPs to efficiently manage security and assists companies with data analysis. It's known for its easy implementation, scalability, real-time monitoring, and extensive integrations. The open-source nature and community support add significant value, making it a popular choice across industries. While highly capable, there is a need for enhancement in dashboard implementation, data integration, and certain advanced features. Licensing, compatibility, and cost-related improvements can further elevate its efficacy.

What are the key features of Elastic Stack?

Powerful Search Capabilities: Offers robust, efficient searching across vast datasets
Scalability: Easily handles large volumes of data
Anomaly Detection: Identifies irregular patterns in data
Machine Learning: Enhances data analysis with intelligent insights
Real-Time Monitoring: Provides up-to-date monitoring of applications and systems
Extensive Integration: Supports diverse tools and solutions

What benefits should users consider?

Ease of Implementation: Quick setup and integration into existing systems
Robust Security: Comprehensive monitoring and analysis capabilities
Community Support: Ongoing improvements and guidance from a dedicated community
Hybrid Deployment: Flexibility in using both cloud and on-premise solutions

In healthcare, Elastic Stack enhances database search capabilities, aiding in patient record management and data retrieval. Managed Security Service Providers use it for comprehensive security management, integrating it with tools like firewalls and authentication systems. Companies benefit from its application in Application Performance Monitoring and its flexibility in adapting to hybrid environments.

Elastic

Sample Customers

VIDCOIN, Wyng, Yellow New Zealand, zipMoney, Cimri, Siemens, Unbabel

Information Not Available

Buyer's Guide

Amazon OpenSearch Service vs. Elastic Stack

December 2025

Free Report: Amazon OpenSearch Service vs. Elastic Stack

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