Amazon OpenSearch Service vs Stackify comparison

Amazon Web Services (AWS) and Stackify are both solutions in the Application Performance Monitoring (APM) and Observability category. Amazon Web Services (AWS) is ranked #25 with an average rating of 7.4, while Stackify is ranked #61. Amazon Web Services (AWS) holds a 2.1% mindshare in APM, compared to Stackify’s 0.2% mindshare. Additionally, 92% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 71% of Stackify users who would recommend it.

Amazon OpenSearch Service

Read 12 Amazon OpenSearch Service reviews

3,841 Views
1,767 Comparison Views

92% willing to recommend

Stackify

Read 6 Stackify reviews

822 Views
477 Comparison Views

71% willing to recommend

Amazon OpenSearch Service

Stackify

Comparison Buyer's Guide

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Executive SummaryUpdated on Aug 11, 2025

Stackify and Amazon OpenSearch Service are major competitors in the observability and monitoring space. Stackify is ahead in terms of ease of use and rapid deployment, while Amazon OpenSearch Service is preferred for its scalability and broader integrations, ideal for large-scale, complex deployments.

Features: Stackify offers powerful monitoring capabilities, quick alert configurations, and comprehensive logging features, making it suitable for immediate deployment. Amazon OpenSearch Service provides advanced data analytics, a robust machine learning framework, and the ability to support complex query requirements, giving it an edge in sophisticated use cases.

Room for Improvement: Stackify could enhance its scalability options and expand integration possibilities to better support larger enterprises. It may also benefit from improved analytics functionality. Amazon OpenSearch Service could improve in ease of use by simplifying its interface and reducing the learning curve. Improvements in deployment speed would also make it more accessible to users with less technical experience.

Ease of Deployment and Customer Service: Stackify stands out with its straightforward deployment process and excellent customer support, which quickens onboarding. Amazon OpenSearch Service, with its detailed documentation and extensive integration support, caters well to experienced teams seeking customization, although its setup may be more complex.

Pricing and ROI: Stackify is often seen as more cost-effective, providing a quicker ROI through its competitive pricing and rapid time-to-value. Amazon OpenSearch Service justifies its higher cost with a powerful feature set and scalability, offering significant long-term value for large-scale operations. Cost-conscious buyers may prefer Stackify, while those prioritizing scalability seek Amazon OpenSearch Service for its advanced features.

To learn more, read our detailed Amazon OpenSearch Service vs. Stackify Report (Updated: August 2025).

Buyer's Guide

Amazon OpenSearch Service vs. Stackify

August 2025

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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 Application Performance Monitoring (APM) and Observability

25th

Ranking in Log Management

20th

Average Rating

7.6

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

Search as a Service (2nd)

Stackify

Ranking in Application Performance Monitoring (APM) and Observability

61st

Ranking in Log Management

61st

Average Rating

7.8

Number of Reviews

Ranking in other categories

IT Infrastructure Monitoring (59th)

Mindshare comparison

As of August 2025, in the Application Performance Monitoring (APM) and Observability category, the mindshare of Amazon OpenSearch Service is 2.1%, up from 0.3% compared to the previous year. The mindshare of Stackify is 0.2%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Application Performance Monitoring (APM) and Observability

Featured Reviews

Johnny Suleiman

MS AWS expert at Bespin Global MEA, an e& enterprise Company

Scalability is a key feature as it allows easy scaling of the platform without downtime

OpenSearch is used as a search engine for specific logs, mainly in e-commerce and monitoring the logs themselves. It is very valuable for e-commerce, enabling data analysis on application logs and customer behavior, and can be integrated with other services, including AI and machine learning…

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Kalyan Somisetty

Senior Developer at PRESIS KONSULT

Simple, easy to configure, and offers trial versions

In the next version, which I want to try, it'll show the comparison of the old responses of the APS. For example, how much time the old response and the new response with the changes. Right now, I cannot differentiate. The graphical interface should be able to capture nicely how much time it has taken and it should be very clear. Sometimes it confuses us. For example, what is this APA for? What were the average responses and how many requests have happened? It needs to give a clear picture. They should enable request and response capturing in the Stackify user interface to show what the request for the APA is. Then, it'll be very good. It should be able to capture the payload. For example, what is the request and what is the response? If it has a nice way of capturing everything then it would be easy. There is no need of using ELK again for logging. As of now, people will use Stackify or maybe Grafana for seeing the stats of the application or responses, however, it doesn't have the capabilities to show everything. People will go for any exception handling or checking the request and response in the ELK. If Stackify can do this future, then it'll be an easier single tool. It is anyway intercepting the logs, application logs. I don't think it's a big matter to capture extra data with the requested response. That requested response capturing also should be configurable since some people want the question response to be captured and for the people that don't want it, we can use that feature. It can be enabled as desired. Many people are using different monitoring tools like ELK, LogStash, and Splunk - many other tools. However, if you can make this kind of performance tool cover everything, then they will not shift to other solutions. It should be easily scalable and configurable in different instances. For example, if the same application is scaled up to differently, it should be easily integrable into Kubernetes pipelines. They should offer plugins to make it more easily integratable. For development enrollment, it should be free to use.

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Quotes from Members

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

Pros

"I would definitely recommend Amazon OpenSearch Service to other professionals due to its fast and reliable search capabilities."

"In case there is a failure, Elastic manages everything well, and there no major downtime."

"They have the good documentation in the help text and that is the reason the Amazon is the perfect solution in the current market."

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

"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."

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

More Amazon OpenSearch Service pros

"The solution is stable and reliable."

"The deployment is very fast."

"The filter feature on Stackify is one of the features I found valuable. It's awesome. When I want to get the application logs, the solution gives me many filters. For example, if I want to get logs from my test environment, the option is there for me to select the environment from Stackify, and you can also select the particular application, and you'll see the information you need there. The filter feature alone and the fact that Stackify offers a lot of different filters is what I like the most about the solution because I've used other tools with the filter feature, but the filtering was very difficult, versus Stackify that has good filtering. On Stackify, you can filter the information by the last one hour, or the last four hours, and you can also select the date range and specify the timestamp, then the solution will give you the information based on the date range you specified. Another feature I found valuable on Stackify is its rating feature because it tells you how your application is faring. For example, a rating of A means excellent, while a rating of F means very bad, or that your application is not doing well at all. The ratings are from A to F. I also like that Stackify helps you in terms of load management because the solution gives you information on overutilized resources. These are the most valuable features of the solution."

"The performance dashboard and the accurate level of details are beneficial."

Cons

"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."

"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."

"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."

"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."

"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."

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

More Amazon OpenSearch Service cons

"It should be easily scalable and configurable in different instances."

"I've not used Stackify for a while, and I'm currently using a solution now that's not as good as Stackify. Among the solutions I've been using so far, Stackify has been one of the best for me, but there's always room for improvement. For example, I don't know if it's just me, but when I try to get the log from Stackify, sometimes it doesn't appear in real-time. It takes a few minutes before the logs appear. When I redeploy my solution and the application starts, I don't see the logs immediately, and it would take two to three minutes before I see the logs. I don't know if other customers have a similar experience. It's the wait time for the logs to appear that's a concern for me, could be improved, and is what the Stackify team should be looking into. In terms of any additional feature that I'd like added to the solution, I'm not sure if Stackify has a way to export logs out. I've been trying to do it. On the solution, you can click on a spiral-like icon and it shows you the entire error, and I'd prefer an export button that would let me download the error and save that into a text file, for example, so it'll be available on my local machine for me to reference it, especially because the log keeps going and as you're using the solution, the system keeps pushing messages on to Stackify, so if I'm looking at a particular error at 12:05 PM, for example, by the time I go back to my system and would like to revisit the error at 12:25 PM, on Stackify, the logs would have gone past that level and I won't see it again which makes it difficult. When you now go back to that timestamp, you don't tend to see it immediately, but if the solution had an export feature for me to save that particular error information on my local machine for reference at a later time, I won't have to go back to Stackify. I just go to that log, specifically to that particular export that I've received on my local machine. I can get it and review it, and it would be easier that way versus me going back to Stackify to find that particular error and request that particular information."

"The search feature could be improved."

"I would like to be able to see metrics about individual running containers on the host machines."

Pricing and Cost Advice

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

"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."

"You only pay for what you use."

"The price is variable. It depends on how much data we have received in that particular month. Usually, it goes up to $2,000, or, at times, $3,000 USD per month."

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

Computer Software Company

13%

Manufacturing Company

Government

Financial Services Firm

15%

Computer Software Company

Media Company

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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?

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 t...

See all answers

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Comparisons

Grafana Loki vs Amazon OpenSearch Service

Compared 26% of the time

Datadog vs Amazon OpenSearch Service

Compared 13% of the time

Amazon CloudWatch vs Amazon OpenSearch Service

Compared 11% of the time

Dynatrace vs Amazon OpenSearch Service

Compared 5% of the time

New Relic vs Amazon OpenSearch Service

Compared 4% of the time

More Amazon OpenSearch Service Competitors

New Relic vs Stackify

Compared 47% of the time

Dynatrace vs Stackify

Compared 32% of the time

Splunk Enterprise Security vs Stackify

Compared 21% of the time

More Stackify Competitors

Product Reports

Buyer's Guide

Amazon OpenSearch Service

August 2025

Download Amazon OpenSearch Service product report

Buyer's Guide

Stackify

July 2025

Download Stackify 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)

Stackify is an application performance management (APM) solution that combines application performance monitoring with logs, errors, and reporting. It is a SaaS solution that is developer-focused. Users can quickly scan, identify, and repair issues with applications. Stackify APM offers valuable tools, such as Prefix and Retrace, which help to make it a comprehensive and valuable APM solution. Stackify is now part of the Netreo family of IT Infrastructure Management (ITIM), which is considered one of the fastest-growing IT organizations in the marketplace today.

Stackify Prefix

Stackify Prefix helps developers write better code, faster. The tool examines, tests, and approves code as it is being written. Almost every new application is code-perfect, negating the need for exhausting troubleshooting and frustrating time-consuming code review.

Prefix is able to discover poor-performing SQL queries, ORM queries, potential bottlenecks, and concealed exceptions prior to moving the application into production.

Prefix offers Summary Dashboards, intuitive suggestions, integrated logs, and distributed tracing. Distributed tracing expands visibility to cloud-native applications, microservices, and containers and can also provide additional transparency to cache services, web services, third-party services, and more. Users are able to easily move from logs to traces and back.

This valuable tool ensures developers are able to consistently release the best code possible in the least amount of time, while improving performance, productivity, and profitability.

Prefix is a very robust and easy-to-use tool. It can be used seamlessly with Linux, macOS, and Windows. Prefix integrates well with numerous languages, such as Java, Python, Ruby, PHP, Node.js, .Net, and .Net Core.

Stackify Retrace

Stackify Retrace is a user-friendly, trusted APM solution used in more than fifty countries worldwide. Users know that Retrace is able to ensure they can complete quicker, more efficient application development and consistently enhance overall application performance by suggesting important intuitive suggestions users need.

This solution is beneficial to both developers (Dev) and operations (Ops) personnel to learn to improve code and immediately finetune issues by:

Establishing effortless collaboration between Dev and Ops personnel via an easy-to-use GUI dashboard.
Delivering complete transparency of all stages of the application development process, from pre-development to production.
Utilizing performance protocols, such as error tracking, application logs, and code profiling, in real time in order to thoroughly understand how long a code will take to complete various tasks.
Improving overall efficiency and productivity by immediately discovering and repairing application issues.

Retrace Real User Monitoring (RUM) uses both front-end and back-end monitoring to give users a complete picture of what is going on with the applications. This intuitive dashboard displays performance with a complete breakdown of resource usage and integrates the server-side and client traces into one engaging, user-friendly, extensive view.

Retrace is an out-of-the-box solution that works seamlessly with Java stacks, PHP, Node.js, Ruby, Python, .Net, and .Net Core. It is also compatible with many of today’s popular frameworks, such as AWS, Azure, Elasticsearch, MongoDB, MySQL, Oracle, PostgreSQL, Redis, and SQL Server. Additionally, Retrace will work effectively with many cloud providers, containers, and languages, and offers excellent and easy integration with today's favorite tools such as Jira, Slack, Jenkins, and more.

Stackify

Sample Customers

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

MyRacePass, ClearSale, Newitts, Carbonite, Boston Software, Children's International, Starkwood Media Group, Fewzion

Buyer's Guide

Amazon OpenSearch Service vs. Stackify

August 2025

Free Report: Amazon OpenSearch Service vs. Stackify

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