Datadog vs Stackify comparison

Datadog and Stackify are both solutions in the Application Performance Monitoring (APM) and Observability category. Datadog is ranked #1 with an average rating of 8.7, while Stackify is ranked #61. Datadog holds a 8.5% mindshare in APM, compared to Stackify’s 0.2% mindshare. Additionally, 97% of Datadog users are willing to recommend the solution, compared to 71% of Stackify users who would recommend it.

Datadog

Read 188 Datadog reviews

26,409 Views
17,166 Comparison Views

97% willing to recommend

Stackify

Read 6 Stackify reviews

822 Views
477 Comparison Views

71% willing to recommend

Datadog

Stackify

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Executive SummaryUpdated on Jul 13, 2025

Datadog and Stackify are competing in the performance monitoring sector. Datadog has an advantage due to its extensive features and integration capabilities. Stackify is preferred for its user-friendly deployment.

Features: Datadog provides real-time infrastructure monitoring, extensive integration, and advanced analytics. Stackify offers code-level tracing, error monitoring, and developer productivity tools.

Room for Improvement: Datadog could improve its user interface complexity and pricing model. Stackify might expand its integration options and enhance its analytics capabilities.

Ease of Deployment and Customer Service: Stackify emphasizes simplicity and quick setups with excellent customer service, suitable for smaller teams. Datadog, while robust for larger infrastructures, involves a steeper learning curve.

Pricing and ROI: Datadog features a higher initial cost that can be justified by its analytics ROI for large enterprises. Stackify is more cost-effective for small teams with quicker ROI due to easy implementation.

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

Buyer's Guide

Datadog 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

Datadog

Ranking in Application Performance Monitoring (APM) and Observability

1st

Ranking in IT Infrastructure Monitoring

2nd

Ranking in Log Management

3rd

Average Rating

8.6

Reviews Sentiment

7.1

Number of Reviews

188

Ranking in other categories

Network Monitoring Software (4th), Container Monitoring (1st), Cloud Monitoring Software (2nd), AIOps (1st), Cloud Security Posture Management (CSPM) (7th)

Stackify

Ranking in Application Performance Monitoring (APM) and Observability

61st

Ranking in IT Infrastructure Monitoring

59th

Ranking in Log Management

61st

Average Rating

7.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2025, in the Application Performance Monitoring (APM) and Observability category, the mindshare of Datadog is 8.5%, down from 10.3% 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

reviewer820579

Senior Product Manager at Redfin Corp

Single pane of glass, easy to share dashboards, and good for monitoring

We've had some issues where we had Datadog automatically turned on in AWS regions that we weren't using, which incurred a small but steady cost that amounted to tens of thousands of dollars spent over a few weeks. I wish there was a global setting that lets an admin restrict which regions DD is turned on in as a default setup step. Sometimes, the APM service dashboard link isn't sharable. I click something in the service catalog, and on that service's APM default view, I try to share a link to that with a teammate, and they reach a blank or error screen. I wish there was more organization and detail in the suggestions when I use the query editor. I'm never quite sure when the autofill dropdown shows up if I'm seeing some custom tag or some default property, so I have to know exactly what I'm looking for in order to build a chart. It's hard to navigate and explore using the query autofill suggestions without knowing exactly what tag to look for. It's been a bit hard to understand how data gets sampled or how many data points a particular dashboard value is using. We've had questions over the RUM metrics that we see and we had to ask for help with how values are calculated, bin sizes, etc to get confidence in our data.

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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

"The ease of correcting these dashboards and widgets when needed is amazing."

"It is a good one stop location where we keep all our data for our infrastructure, and it's also easier to navigate between different things."

"For us to have visibility into our app stack and the hardware we run has been highly beneficial."

"This spectrum of solutions has allowed us to track down bugs faster and more rapidly, which allows us to limit revenue lost during downtime."

"The most valuable features are logging, the extensive set of integrations, and easy jumpstart."

"The product has offered increased visibility via logging APM, metrics, RUM, etc."

"We integrate our application logs. It is great to be able to tie our metrics and our traces together."

"The initial setup was straightforward from my own experience, helping integrate within the application and service levels."

More Datadog pros

"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."

"The solution is stable and reliable."

Cons

"I found the solution to be stable, I did not experience any bugs or glitches. However, some of the managing team did."

"Delta traces on the Golang profiler are extremely expensive concerning memory utilization."

"Stability of the product has been a concern for us outside of the primary monitoring agents."

"I've found that the documentation is lacking in certain regards."

"Datadog is expensive."

"The documentation could be improved regarding setting up the agent properly and debugging."

"If there were a more cost-effective manner of deploying the tool, we'd be more likely to adopt it more widely."

"The product needs a better Datadog agent installation."

More Datadog cons

"The search feature could be improved."

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

"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."

Pricing and Cost Advice

"Our licensing fees are paid on a monthly basis."

"My advice is to really keep an eye on your overage costs, as they can spiral really fast."

"Pricing seemed easy until the bill came in and some things were not accounted for."

"Pricing is somewhat affordable compared to other solutions but in order to really lower the costs of other products you need to plan very carefully your resources usage, otherwise, it can get expensive real quick."

"It has a module-based pricing model."

"The price is better than some competing products."

"It didn't scale well from the cost perspective. We had a custom package deal."

"I am not satisfied with its licensing. Its payment is based on the exported data, and there was an explosion of the data for three or four weeks. My customer was not alerted, and there was no way for them to see that there has been an explosion of data. They got a big invoice for one or two months. The pricing model of Datadog is based on the data. The customer was quite surprised about not being alerted about this explosion of data. They should provide some kind of alert when there is an increase in usage."

More Datadog pricing and cost advice

"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

15%

Computer Software Company

14%

Manufacturing Company

Healthcare Company

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

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...

See all answers

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...

See all answers

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 ...

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Comparisons

Dynatrace vs Datadog

Compared 11% of the time

Azure Monitor vs Datadog

Compared 9% of the time

Splunk Enterprise Security vs Datadog

Compared 5% of the time

AWS X-Ray vs Datadog

Compared 4% of the time

New Relic vs Datadog

Compared 4% of the time

More Datadog 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

Datadog

August 2025

Download Datadog product report

Buyer's Guide

Stackify

July 2025

Download Stackify product report

Overview

Datadog is a comprehensive cloud monitoring platform designed to track performance, availability, and log aggregation for cloud resources like AWS, ECS, and Kubernetes. It offers robust tools for creating dashboards, observing user behavior, alerting, telemetry, security monitoring, and synthetic testing.

Datadog supports full observability across cloud providers and environments, enabling troubleshooting, error detection, and performance analysis to maintain system reliability. It offers detailed visualization of servers, integrates seamlessly with cloud providers like AWS, and provides powerful out-of-the-box dashboards and log analytics. Despite its strengths, users often note the need for better integration with other solutions and improved application-level insights. Common challenges include a complex pricing model, setup difficulties, and navigation issues. Users frequently mention the need for clearer documentation, faster loading times, enhanced error traceability, and better log management.

What are the key features of Datadog?

Graphs and Dashboards: Visualizes servers and infrastructure with customizable views.
Metrics: Offers deep insights into system performance and user behavior.
Log Management: Provides powerful analytics for logs and seamless log aggregation.
Unified Tagging: Facilitates organization and retrieval of metrics and logs.
APM and RUM: Enables application performance monitoring and real user monitoring for comprehensive insights.
Synthetic Testing: Allows the simulation of user interactions to test application performance.

What benefits and ROI should users look for in reviews?

System Reliability: Helps ensure uptime and performance across cloud environments.
Proactive Issue Resolution: Assists in identifying and resolving issues before they impact users.
Operational Efficiency: Streamlines monitoring and log management tasks.
Flexible Integrations: Adapts to various cloud services and infrastructure setups.
Real-Time Alerts: Provides timely notifications to address problems swiftly.

Datadog is implemented across different industries, from tech companies monitoring cloud applications to finance sectors ensuring transactional systems' performance. E-commerce platforms use Datadog to track and visualize user behavior and system health, while healthcare organizations utilize it for maintaining secure, compliant environments. Every implementation assists teams in customizing monitoring solutions specific to their industry's requirements.

Datadog

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

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

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

Buyer's Guide

Datadog vs. Stackify

August 2025

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