Datadog vs. Request Metrics

As per my experience, Datadog is best suited for complex, cloud-native environments where unified observability is critical, as it integrates seamlessly with AWS and Azure. Moreover, it provides deep visibility into latency and error rates. Datadog pricing is less appropriate for Startups with a tight budget and for organizations needing advanced incident management.

Incentivized

Request Metrics is great for small web development teams that want to make fast web applications. It was quick for us to get started and we could use the reports right away without having to read through documentation. If you just need to get some performance metrics, Request Metrics is perfect. It would not be so good for a larger team or a complex backend application as it is pretty limited in what it can measure.

• 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.

Incentivized

• Performance charts are really simple and easy for us to understand what is happening
• It was easy to get started and doesn't need administration or training
• It's affordable for our team
• It's fast

• In my experience, .NET Tracing Agent caused severe and untraceable performance issues
• In my opinion, usage and billing structures were opaque and surprising
• In my experience, documentation was incomplete, contradicting or sometimes completely wrong, even for common infrastructure (AWS Fargate)
• I feel support was unhelpful at times, and bounced us back and forth to other teams
• In my opinion, multiple methods of sample rate control were ineffective, adding to excessive usage and cost

Incentivized

• I wish that it could also do uptime checking of the site
• There is not enough detail to drill into individual users

Definitely will not revisit after our issues and, in my opinion, poor support.

Incentivized

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.

Incentivized

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.

Incentivized

Documentation was difficult to work through, rollout was catastrophic (completely outage)

Incentivized

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.

Incentivized

We also consider Speedcurve and Calibre for monitoring. Speedcurve was really nice, but the reports were slow. We had to wait a lot to get information. It was also out of our budget and would require extra justification to use it. Calibre was also nice, but the numbers were based on synthetic rather than real user performance. We felt that this wasn't as helpful for us.

• 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.

Incentivized

• The launch of our project dashboard was much smoother and more successful because we could fix problems earlier
• It fit without our existing operations budget