Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Mesos
Score 2.6 out of 10
N/A
N/AN/A
Datadog
Score 8.6 out of 10
N/A
Datadog is a monitoring service for IT, Dev and Ops teams who write and run applications at scale, and want to turn the massive amounts of data produced by their apps, tools and services into actionable insight.
$18
per month per host
Pricing
Apache MesosDatadog
Editions & Modules
No answers on this topic
Log Management
$1.27
per month (billed annually) per host
Infrastructure
$15.00
per month (billed annually) per host
Standard
$18
per month per host
Enterprise
$27
per month per host
DevSecOps Pro
$27
per month per host
APM
$31.00
per month (billed annually) per host
DevSecOps Enterprise
$41
per month per host
Offerings
Pricing Offerings
MesosDatadog
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeOptional
Additional DetailsDiscount available for annual pricing. Multi-Year/Volume discounts available (500+ hosts/mo).
More Pricing Information
Community Pulse
Apache MesosDatadog
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User Ratings
Apache MesosDatadog
Likelihood to Recommend
2.0
(2 ratings)
9.4
(55 ratings)
Usability
-
(0 ratings)
9.2
(34 ratings)
Support Rating
1.0
(1 ratings)
8.9
(6 ratings)
User Testimonials
Apache MesosDatadog
Likelihood to Recommend
Apache
There's really no reason to ever use Mesos. We switched over to Kubernetes and it's been a breath of fresh air - better CD support, easy CLI for browsing logs, no mysterious dangling redeploys. If you're looking for a tool to manage a fleet of Docker containers on VMs, Kubernetes beats Mesos by a wide margin.
Read full review
Datadog
Datadog may be better suited for teams that have a more out-of-the-box infrastructure, on the primary platforms Datadog supports. You may also have better results if you have a bigger team dedicated to devops and/or a bigger budget. We found that trying to adapt it to our use case (small team, .NET on AWS Fargate) wasn't feasible. We continually ran into roadblocks that required us to dig through documentation (and at times, having to figure out some documentation was wrong), go back and forth with support, and in my opinion, waste money on excessive and unintended usages due to opaque pricing models and inaccurate usage reports, as well as broken/non-functional rate sampling controls.
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Pros
Apache
  • Mesos may have many frameworks. If you have Mesos installed on your servers, you may use it for many kinds of tasks. Today we're running only web applications but the idea is to install a different framework for big data soon.
  • There is a good community growing around it.
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Datadog
  • The thing which Datadog does really well, one of them are its broad range of services integrations and features which makes it one step observability solution for all. We can monitor all types of our application, infrastructure, hosts, databases etc with Datadog.
  • Its custom dashboard feature which helps us to visualize the data in a better way . It supports different types of charts through those charts we can create our dashboard more attractive.
  • Its AI powered alerting capability though that we can easily identify the root cause and also it has a low noise alerting capability which means it correlated the similar type of issues.
Read full review
Cons
Apache
  • Unreliable deployments that would fail for no good reason. Sometimes our Docker container would be "restarting" forever because Mesos thought it didn't have enough resources to start the container.
  • Impossibly slow UI. Built in React under the hood with a lot of bloatware backed in, so loading the Mesos UI on a slow internet connection was painful.
  • No real logging solution - it would stream "console.log()" output to the UI, but searching for logs wasn't really possible without downloading a huge file.
  • No built-in support for redeploying containers from a CI. We had to create a service whose whole job was to expose an HTTP endpoint that restarted a container, and then made Circle CI ping the endpoint whenever we wanted to redeploy.
Read full review
Datadog
  • Alert windows cause lag in notifications (e.g. if the alert window is X errors in 1 hour, we won't get alerted until the end of the 1 hour range)
  • I would appreciate more supportive examples for how to filter and view metrics in the explorer
  • I would like a more clear interface for metrics that are missing in a time frame, rather than only showing tags/etc. for metrics that were collected within the currently viewed time frame
Read full review
Likelihood to Renew
Apache
No answers on this topic
Datadog
Definitely will not revisit after our issues and, in my opinion, poor support.
Read full review
Usability
Apache
No answers on this topic
Datadog
There are so many features that it can be hard to figure out where you need to go for your own use case. For example, RUM monitoring us buried in a "Digital Experience" sidebar setting when this is one of our key use cases that I sometimes struggle to find in the application. It appears that ECS + Fargate monitoring was recently released which is great because we had to build a lambda reporting solution for ephemeral task monitoring. But this new feature was never on my radar until I starting clicking around the application.
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Support Rating
Apache
No real support channel, the Mesos GitHub issues list was the only one we found and it wasn't particularly helpful.
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Datadog
The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.
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Implementation Rating
Apache
No answers on this topic
Datadog
Documentation was difficult to work through, rollout was catastrophic (completely outage)
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Alternatives Considered
Apache
Kubernetes is really great and their community is growing really fast (Google influence). We evaluated it in the beginning and it would fit for our web applications workload. We decided to proceed with Mesos because it has more potential. You may use a different framework for different kinds of tasks on Mesos. There is a Kubernetes framework for Mesos, by the way.
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Datadog
Our logs are very important, and Datadog manages them exceptionally well. We frequently use Datadog services for our investigations. Use case: Monitor your apps, infrastructure, APIs, and user experience.


Key features:


Logs, metrics, and APM (Application Performance Monitoring)


Real-time alerting and dashboards


Supports Kubernetes, AWS, GCP, and other integrations


RUM (Real User Monitoring) and Synthetics





✅ Best for backend, server, and distributed systems monitoring.
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Return on Investment
Apache
  • It's optimizing our resources.
  • It's improving our process. This argument is not just for Mesos, but we needed a tool like this to start changing and it works like a charm.
  • It's open source.
Read full review
Datadog
  • Saved us (time & money) from developing our own monitoring utilities that would pale in comparison
  • Alerts allow us to remedy issues before our customers even know about them
  • Tracking resource usage over time allows us to better plan for future needs, before it becomes a pain-point.
Read full review
ScreenShots

Datadog Screenshots

Screenshot of the out-of-the-box and customizable monitoring dashboards.Screenshot of Datadog's collaboration features, where users can discuss issues in-context with production data, annotate changes and notify their teams, see who responded to that alert before, and discover what was done to fix it.Screenshot of where Datadog unifies traces, metrics, and logs—the three pillars of observability.Screenshot of some of Datadog's 400+ built-in integrations.Screenshot of Datadog's Service Map, which decomposes an application into all its component services and draws the observed dependencies between these services in real timeScreenshot of centralized log data, pulled from any source.