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Datadog vs Mezmo comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Aug 3, 2025

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 Log Management
4th
Average Rating
8.6
Reviews Sentiment
7.0
Number of Reviews
206
Ranking in other categories
Network Monitoring Software (4th), IT Infrastructure Monitoring (3rd), Container Monitoring (2nd), Cloud Monitoring Software (2nd), AIOps (1st), Cloud Security Posture Management (CSPM) (6th)
Mezmo
Ranking in Application Performance Monitoring (APM) and Observability
75th
Ranking in Log Management
50th
Average Rating
9.0
Number of Reviews
2
Ranking in other categories
Observability Pipeline Software (7th)
 

Mindshare comparison

As of October 2025, in the Application Performance Monitoring (APM) and Observability category, the mindshare of Datadog is 7.4%, down from 10.4% compared to the previous year. The mindshare of Mezmo is 0.3%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Application Performance Monitoring (APM) and Observability Market Share Distribution
ProductMarket Share (%)
Datadog7.4%
Mezmo0.3%
Other92.3%
Application Performance Monitoring (APM) and Observability
 

Featured Reviews

Dhroov Patel - PeerSpot reviewer
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.
TO
It consolidates all logs into one place and provides required features and functionalities
Every once in a while, our IBM cloud operational implementation gets behind. Sometimes, when we have a customer event, we do not get access to the latest logs for about 30 minutes, particularly for the sites that are heavily utilized. This is clearly not good. It is impossible to do RCA when you can't look at the logs that pertain to the time period in which the event occurred. It could be more of an operational problem than a feature problem. I don't have visibility about whether it is a LogDNA issue or just an operational issue.

Quotes from Members

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

Pros

"Thanks to frequent concurrent deployments, the DataDog alerts monitors allow us quickly detect issues if anything occurs."
"Flame graphs are pretty useful for understanding how GraphQL resolves our federated queries when it comes to identifying slow points in our requests. In our microservice environment with 170 services."
"Datadog is constantly adding new features."
"Datadog has given us near-live visibility across our entire cloud platform."
"Synthetic testing has been a game-changer, allowing us to catch potential problems before they impact real users."
"We rely heavily on the API crawlers that Datadog uses for cloud integrations. These allow us to pick up and leverage the tags teams have already deployed without having also to make them add them at the agent level."
"It has a nice UI."
"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."
"The solution aggregates all event streams, so that if there are any issues, it's all in the same interface."
"LogDNA consolidates all logs into one place, which is super valuable."
 

Cons

"Logging is not a great experience."
"When the logs are too big, and Datadog splits them, the JSON format breaks and it is not so useful for us."
"Datadog needs more local Asia-Pacific support, and if they don't have a SaaS solution in Asia-Pacific, they should offer an on-prem version. I'm told that's not possible."
"Datadog could improve the flexibility with AI and ML concepts. This will allow customers to be more leveraged towards publishing."
"It is far too easy to run up huge unexpected costs."
"The cost is pretty high."
"We need a lot of modules since we collect all data logs from all operating systems."
"In the past two years, there have been a couple of outages."
"Every once in a while, our IBM cloud operational implementation gets behind. Sometimes, when we have a customer event, we do not get access to the latest logs for about 30 minutes, particularly for the sites that are heavily utilized. This is clearly not good. It is impossible to RCA when you can't look at the logs that pertain to the time period in which the event occurred. It could be more of an operational problem than a feature problem. I don't have visibility about whether it is a LogDNA issue or just an operational issue."
"No ability to encapsulate a query or a filter, and communicate or share that among the team."
 

Pricing and Cost Advice

"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 didn't scale well from the cost perspective. We had a custom package deal."
"The solution's pricing depends on project volume."
"It costs the same amount it would if we were hosting it ourselves, so we are incredibly happy with the cost."
"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."
"My advice is to really keep an eye on your overage costs, as they can spiral really fast."
"The solution is fairly priced but history and log storage can get costly depending on your needs."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Computer Software Company
14%
Manufacturing Company
8%
Retailer
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business80
Midsize Enterprise46
Large Enterprise94
No data available
 

Questions from the Community

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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

 

Also Known As

No data available
LogDNA
 

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
Instacart, Asics, Lime, Salesforce
Find out what your peers are saying about Datadog vs. Mezmo and other solutions. Updated: September 2025.
872,706 professionals have used our research since 2012.