Coralogix vs. Datadog

Most Appropriate: Searching for logs, setting alerts on anomalies, multiple container for logs separated by multiple services. Classification of different types of logs. Tracing of requests involving multiple services. Finding the time between different endpoints in the service layer to identify the choke points. Less Appropriate: Duplication of logs can cause an issue for you.

Incentivized

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

• Unified platform for logs and traces.
• Enable alerts on anomalies.
• Intuitive interface.

Incentivized

• 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

• Login issue with SSO: In some cases, the SSO login button is not visible on the Login page. This causes issue to access Coralogix.
• Duplicate Logs: In some cases, we get duplicate logs in Coralogix and it becomes difficult to identify if these are duplicate logs.
• Sometimes the tracing feature has glitches

Incentivized

• 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

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

Incentivized

The product is easy to use and integrate. The customer support is at a level of its own. There was never a time we needed help with something, and the support wasn't there to provide all the help needed in a very effective and efficient way. Being proactive, suggesting ways to solve and not just answering questions, and providing more knowledge about how the product should be used.

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

Think of Coralogix as a proactive teammate rather than just a passive tool. Unlike Datadog or New Relic, where you often pay a steep "tax" to index noise just to catch one error, Coralogix analyzes logs in-stream—saving you from surprise bills when containers get noisy. Its automatic clustering spots hidden issues without you writing endless rules, giving you instant clarity where others force you to dig.

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

• Faster time to resolve issues.
• Ability to detect issues before our users.

Incentivized

• 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