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Datadog vs Stackify comparison

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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
3rd
Ranking in IT Infrastructure Monitoring
3rd
Ranking in Log Management
4th
Average Rating
8.6
Reviews Sentiment
6.9
Number of Reviews
211
Ranking in other categories
Network Monitoring Software (9th), Container Monitoring (3rd), Cloud Monitoring Software (1st), AIOps (2nd), Cloud Security Posture Management (CSPM) (8th), AI Observability (1st)
Stackify
Ranking in Application Performance Monitoring (APM) and Observability
62nd
Ranking in IT Infrastructure Monitoring
68th
Ranking in Log Management
56th
Average Rating
7.8
Number of Reviews
6
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of November 2026, in the Application Performance Monitoring (APM) and Observability category, the mindshare of Datadog is 4.1%, down from 6.6% compared to the previous year. The mindshare of Stackify is 0.8%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Application Performance Monitoring (APM) and Observability Mindshare Distribution
ProductMindshare (%)
Datadog4.1%
Stackify0.8%
Other95.1%
Application Performance Monitoring (APM) and Observability
 

Featured Reviews

Kallamuddin Ansari - PeerSpot reviewer
Cyber Security Consultant at HR Software Solution
Unified monitoring has improved incident response and now reduces root cause analysis time
One area where Datadog can be improved is around alert quality. In the beginning, it tends to generate many alerts, and without proper tuning, many of them are not actionable. It would help if there were more built-in guidance or smarter defaults to reduce noise. Another improvement area is cost visibility and control. As log and metric ingestion increases, it has not always been straightforward to track which data is driving the cost. More granular and real-time cost insights would make it easier to manage. Additionally, while the dashboards are flexible, navigating and organizing them at scale can become slightly difficult. Better structuring or management options would help in larger environments.
Moses Arigbede - PeerSpot reviewer
Head of DevOps at Partsimony
Easy to set up with great custom dashboards but needs to improve non-.NET infrastructure
They need to improve non-.NET infrastructure. We always had difficulty when it comes to reporting or metrics that come from Linux operating systems and Docker containers. For anything that runs within the Unix environment, we always had problems with them, however, if it was a document-based application, Stackify was 100%, it gave everything. Now, the aggregation agent, the metric agent for Stackify for Linux, collects everything. When I say everything, I mean, everything. It collects so much information that we now started to term it as useless data as all that ingestion will just come in and overwhelm your log retention limit for the month and really this spike up your cost at the end of the month. You'll need to do a lot in order to train down the data coming in from all your Linux environments, to get to what you really need, which actually takes some time as well. I would like to be able to see metrics about individual running containers on the host machines. Stackify has not really gotten that right, as far as I'm concerned. Netdata has done a better job and New Relic has also done a better job. They need to improve on that. We need to be able to see the individual resource usage of containers running within a particular host.

Quotes from Members

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

Pros

"We have been impressed with the uptime and clean and light resource usage of the agents."
"Datadog dashboards are pretty great."
"It has provided visibility with ease of implementation and allowed multiple teams to quickly onboard it."
"Customizable views as well as the ability to "dive in" when we see someting anomalous has improved the workflow for handling incidents."
"Several critical dashboards were created years ago and are still in use today."
"Datadog has impacted our organization positively since we were previously using AppDynamics and then we switched to Datadog, which improved a lot in our alerting and monitoring in the infrastructure space and application space, allowing us to monitor business transactions and take proactive action before an end user reports it."
"Datadog has positively impacted my organization by allowing for a more proactive response to issues whenever they occur."
"The greatest impact it has had is on the ability to democratize observability and put monitoring into the hands of the people."
"It is very simple and very easy to configure."
"The solution is stable and reliable."
"The performance dashboard and the accurate level of details are beneficial."
"We switched from New Relic and Loggly as it provides us more info at a lower price."
"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."
"Within few hours of install we've identify the source of issue we've been investigating for few days and couldn't pin point."
"What stood out to us were the metrics and granular details we received."
 

Cons

"I think Datadog can be improved by continually finding errors and making things easy to see and customize."
"Once agents are connected to the Datadog portal, we should be able to upgrade them quickly."
"I'm not sure what kind of features are in the roadmap right now, but I encourage the development of features for defining your organization, and allowing the visibility of what kind of metrics you can get. Those features would be really useful for us."
"The pricing model seems to escalate quickly with increasing metrics ingestion and monitoring across clouds."
"The solution needs to integrate AI tools."
"Datadog has become significantly slower over the last year. They could improve performance at the risk of slowing down feature work."
"I sometimes log in and see items changed, either in the UI or a feature enabled. To see it for the first time without proper communication can sometimes come as a shock."
"It is far too easy to run up huge unexpected costs."
"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."
"Better mobile support."
"I would like to be able to see metrics about individual running containers on the host machines."
"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."
"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."
"The search feature could be improved."
"It's not easy to set up. It's hard especially for juniors to understand."
 

Pricing and Cost Advice

"The solution is fairly priced but history and log storage can get costly depending on your needs."
"​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."
"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."
"The solution's pricing depends on project volume."
"It didn't scale well from the cost perspective. We had a custom package deal."
"Datadog does not provide any free plans to use the solution. When I start with a proof of concept it would be sensible to have a free plan to test the tool and check whether it fits the requirements of the project. Before the production stage, it is always good to have a free plan with some limited features, number of requests, or logs."
"At my last company, we did see ROI, specifically around response time. We could get to mission critical things that were down and losing revenue on immediately. So, the product paid itself back."
"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."
"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
13%
Manufacturing Company
10%
Outsourcing Company
8%
Comms Service Provider
7%
Comms Service Provider
20%
Construction Company
19%
Outsourcing Company
8%
Performing Arts
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business81
Midsize Enterprise50
Large Enterprise100
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise2
Large Enterprise2
 

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...
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: October 2026.
920,939 professionals have used our research since 2012.