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 #22 with an average rating of 7.3, while Stackify is ranked #63. Amazon Web Services (AWS) holds a 1.1% mindshare in APM, compared to Stackify’s 0.7% 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 13 Amazon OpenSearch Service reviews

7,043 Views
3,381 Comparison Views

92% willing to recommend

Stackify

Read 6 Stackify reviews

2,566 Views
1,309 Comparison Views

71% willing to recommend

Amazon OpenSearch Service

Stackify

Comparison Buyer's Guide

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Executive SummaryUpdated on Feb 22, 2026

Stackify and Amazon OpenSearch Service compete in data management and analysis. While Stackify excels in user-friendliness, Amazon OpenSearch Service stands out with scalability and robust infrastructure.

Features: Stackify offers integrated error tracking, log management, and real-time application monitoring in a single platform. Amazon OpenSearch Service provides extensive scalability, open-source capabilities, and advanced log analytics. Stackify simplifies troubleshooting, while Amazon focuses on large-scale data exploration.

Room for Improvement: Stackify could enhance scalability and infrastructure robustness. It may also benefit from more customizable features and integrations with other platforms. Amazon OpenSearch Service might simplify its deployment process, improve user interface intuitiveness, and provide more specialized customer support options.

Ease of Deployment and Customer Service: Stackify is notable for quick deployment and proactive customer support. Its integration process is streamlined, facilitating rapid setup. Amazon OpenSearch Service offers comprehensive support documentation and a global customer service network, though its deployment can be more complex, focusing on performance flexibility.

Pricing and ROI: Stackify features a straightforward pricing model, which is economical for smaller teams and offers quicker ROI due to its focused feature set. Amazon OpenSearch Service, while potentially more costly, has a scalable pricing model appealing to larger enterprises, promising significant ROI for those interested in expansive data analytics solutions.

To learn more, read our detailed Amazon OpenSearch Service vs. Stackify Report (Updated: April 2026).

Buyer's Guide

Amazon OpenSearch Service vs. Stackify

April 2026

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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

22nd

Ranking in Log Management

18th

Average Rating

7.6

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Search as a Service (3rd)

Stackify

Ranking in Application Performance Monitoring (APM) and Observability

63rd

Ranking in Log Management

58th

Average Rating

7.8

Number of Reviews

Ranking in other categories

IT Infrastructure Monitoring (66th)

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 Stackify is 0.7%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Application Performance Monitoring (APM) and Observability Mindshare Distribution
Product	Mindshare (%)
Amazon OpenSearch Service	1.1%
Stackify	0.7%
Other	98.2%

Application Performance Monitoring (APM) and Observability

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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Idoko Emmanuel

Senior Software Engineer at a tech services company with 1,001-5,000 employees

Has good filtering and rating features and helps with resource and load management

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.

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

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

"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"

"It's a good log management platform. In terms of infrastructure management, it's good."

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

"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."

"Amazon OpenSearch Service has enhanced our organization's ability to store and search large amounts of data efficiently."

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

More Amazon OpenSearch Service pros

"What stood out to us were the metrics and granular details we received."

"Within few hours of install we've identify the source of issue we've been investigating for few days and couldn't pin point."

"The solution is stable and reliable."

"My advice to anyone who wants to use Stackify is to go for it because my experience with it is good."

"It is very simple and very easy to configure."

"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."

"We switched from New Relic and Loggly as it provides us more info at a lower price."

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

More Stackify pros

Cons

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

"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."

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

"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."

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

"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."

More Amazon OpenSearch Service cons

"One thing that happens as a new user on Stackify is when you install the agent it pulls everything and if you're not careful, your log allowance will just be exhausted as you are actually pulling too much data."

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

"It's not easy to set up. It's hard especially for juniors to understand."

"Better mobile support."

"I'm looking to see more performance tools, but heard that they are going to release some."

"Another improvement would be the agent memory utilization, which led to our recent reevaluation."

"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."

More Stackify cons

Pricing and Cost Advice

"Compared to other cloud platforms, it is manageable and not very expensive."

"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."

"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%

Manufacturing Company

10%

Computer Software Company

10%

Government

Construction Company

19%

Comms Service Provider

14%

Media Company

Performing Arts

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	3
Midsize Enterprise	2
Large Enterprise	2

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

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Comparisons

Grafana Loki vs Amazon OpenSearch Service

Compared 9% of the time

Xapien vs Amazon OpenSearch Service

Compared 6% of the time

Datadog vs Amazon OpenSearch Service

Compared 5% of the time

Amazon CloudWatch vs Amazon OpenSearch Service

Compared 4% of the time

Azure AI Search vs Amazon OpenSearch Service

Compared 4% of the time

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New Relic vs Stackify

Compared 7% of the time

Splunk Enterprise Security vs Stackify

Compared 5% of the time

Dynatrace vs Stackify

Compared 5% of the time

DX Spectrum vs Stackify

Compared 4% of the time

Splunk AppDynamics vs Stackify

Compared 4% of the time

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Product Reports

Buyer's Guide

Amazon OpenSearch Service

May 2026

Download Amazon OpenSearch Service product report

Buyer's Guide

Stackify

April 2026

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 enhances application performance monitoring with features like detailed logging and effective filtering options, integrating capabilities to eliminate the need for multiple tools, and providing rapid deployment and stable performance.

Stackify offers a comprehensive solution for business insight through custom dashboards, error monitoring, load management, and application scoring. Its ability to visualize performance by creating responsive dashboards helps connect business and technical teams. Despite its strengths, users seek improvements such as better mobile support, real-time log appearance, and Docker documentation. Enhanced Linux support and agent memory optimization are also desired, along with better visibility into container and application performance metrics. Integrating more plugins and options would make Stackify a more robust monitoring tool.

What are the key features of Stackify?

Detailed Log and Error Data: Provides in-depth traces and logs for error and data analysis.
Custom Dashboards: Offers business insights and application scoring through tailored dashboards.
Performance Metrics: Monitors application and server performance effectively.
Simple Configuration: Ensures easier setup and deployment without complexities.
Filtering Options: Enables effective management of logs and errors through filters.

What benefits should be expected from using Stackify?

Improved Performance Monitoring: Provides tools to identify root causes and enhance application and server monitoring.
Resource Management: Manages server utilization and handles resource spikes efficiently.
Proactive Alerts: Allows setting up alerts across platforms like AWS and Docker.
Log Aggregation: Compiles logs for testing and analysis to improve system performance.

Organizations across industries use Stackify for extensive application performance monitoring, particularly in testing environments. It is crucial for analyzing database calls, third-party requests, and aggregating logs. Its capabilities in monitoring across AWS and Docker environments make it especially valuable for dynamic and distributed infrastructures.

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

April 2026

Free Report: Amazon OpenSearch Service vs. Stackify

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