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Datadog vs Stackify comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 25, 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

Datadog
Ranking in Application Performance Monitoring (APM) and Observability
1st
Ranking in IT Infrastructure Monitoring
2nd
Ranking in Log Management
4th
Average Rating
8.6
Reviews Sentiment
7.0
Number of Reviews
210
Ranking in other categories
Network Monitoring Software (4th), Container Monitoring (3rd), Cloud Monitoring Software (1st), AIOps (1st), Cloud Security Posture Management (CSPM) (5th), AI Observability (1st)
Stackify
Ranking in Application Performance Monitoring (APM) and Observability
63rd
Ranking in IT Infrastructure Monitoring
66th
Ranking in Log Management
58th
Average Rating
7.8
Number of Reviews
6
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of May 2026, in the Application Performance Monitoring (APM) and Observability category, the mindshare of Datadog is 4.7%, down from 9.3% 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
ProductMindshare (%)
Datadog4.7%
Stackify0.7%
Other94.6%
Application Performance Monitoring (APM) and Observability
 

Featured Reviews

Dhroov Patel - PeerSpot reviewer
Site Reliability Engineer at Grainger
Has improved incident response with better root cause visibility and supports flexible on-call scheduling
Datadog needs to introduce more hard limits to cost. If we see a huge log spike, administrators should have more control over what happens to save costs. If a service starts logging extensively, I want the ability to automatically direct that log into the cheapest log bucket. This should be the case with many offerings. If we're seeing too much APM, we need to be aware of it and able to stop it rather than having administrators reach out to specific teams. Datadog has become significantly slower over the last year. They could improve performance at the risk of slowing down feature work. More resources need to go into Fleet Automation because we face many problems with things such as the Ansible role to install Datadog in non-containerized hosts. We mainly want to see performance improvements, less time spent looking at costs, the ability to trust that costs will stay reasonable, and an easier way to manage our agents. It is such a powerful tool with much potential on the horizon, but cost control, performance, and agent management need improvement. The main issues are with the administrative side rather than the actual application.
IE
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.

Quotes from Members

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

Pros

"Datadog is easy to use and easy to deploy. It's a better solution compared to others on the market in terms of being budget friendly for our customers."
"Datadog infrastructure monitoring has helped us identify health issues with our virtual machines, such as high load, CPU, and disk usage, as well as monitoring uptime and alerting when Kubernetes containers have a bad time staying up."
"While my team is relatively new to Datadog, I already see immense value in switching over to Datadog as the primary APM and NPM tool."
"Customizable views as well as the ability to "dive in" when we see someting anomalous has improved the workflow for handling incidents."
"We like the distributed tracing and flame graphs for debugging. This has been invaluable for us during periods of high traffic or red alert conditions."
"The full stack of integrations made it easier to monitor the different technologies and platform providers, including Software as a Service providers, that otherwise would need a lot of work and customization to be able to see what is happening."
"It has scaled great. I haven't run into any problems anywhere that I've used it. They have handled everything that we have needed them to."
"APM and tracing are super useful."
"We switched from New Relic and Loggly as it provides us more info at a lower price."
"My advice to anyone who wants to use Stackify is to go for it because my experience with it is good."
"The performance dashboard and the accurate level of details are beneficial."
"Within few hours of install we've identify the source of issue we've been investigating for few days and couldn't pin point."
"It is very simple and very easy to configure."
"What stood out to us were the metrics and granular details we received."
"The solution is stable and reliable."
"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."
 

Cons

"The product is quite complex, and there are so many features that I either didn't know about or wasn't sure how to use."
"Datadog probably didn't save me a ton of time because there are so many replay videos that I had to sort through in order to find the particular sales reps that I'm looking for for our beta test group."
"Additional metrics should be included."
"I believe Datadog could be improved because sometimes it's not the most user-friendly, and when monitors have a new metric or a service that no longer needs to be monitored, it remains in the system."
"It is very difficult to make the solutions fit perfectly for large organizations, especially in terms of high cardinality objects and multi-tenancy, where the data needs to be rolled up to a summarized level while maintaining its individual data granularity and identifiers."
"We primarily use the log management functionality, and the only feedback I have there is better fuzzy text searching in logs (the kind that Kibana has)."
"In some ways, the tool has a pretty steep learning curve. Discovering the various capabilities available, then learning how to utilize them for particular use cases can be challenging."
"We want to reduce having to go to different screens to obtain all the information."
"Better mobile support."
"It's not easy to set up. It's hard especially for juniors to understand."
"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."
"Another improvement would be the agent memory utilization, which led to our recent reevaluation."
"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 should be easily scalable and configurable in different instances."
"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."
 

Pricing and Cost Advice

"While it is an expensive product, I would rate the pricing level at four out of five."
"The solution's pricing depends on project volume."
"The cost is high and this can be justified if the scale of the environment is big."
"Sometimes it's very hard to project how much it will cost for the monthly subscription for the next month when you add certain features. Having better visibility of the cost would give a better experience."
"​Pricing seems reasonable. It depends on the size of your organization, the size of your infrastructure, and what portion of your overall business costs go toward infrastructure."
"The tool is open-source."
"They prefer monthly subscriptions."
"It is easy to run up a large bill, so become familiar with the cost of each piece of your bill and use the metrics they supply to estimate and monitor your bill."
"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
14%
Computer Software Company
9%
Manufacturing Company
8%
Healthcare Company
6%
Construction Company
19%
Comms Service Provider
14%
Media Company
9%
Performing Arts
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business82
Midsize Enterprise47
Large Enterprise100
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise2
Large Enterprise2
 

Questions from the Community

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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...
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

 

Overview

 

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
Find out what your peers are saying about Datadog vs. Stackify and other solutions. Updated: April 2026.
893,221 professionals have used our research since 2012.