We performed a comparison between Azure Monitor and Datadog based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Datadog finishes ahead of Azure Monitor. Users feel Datadog gives the best visibility, better integration, and helpful, timely support. The logs and error reporting are extremely useful to conduct analysis and root cause analysis. The setup, ease of use, and flexibility with dashboard creation and reporting are just some of the things that our users like best about Datadog.
"The tool's most valuable feature is the alert system, which can be set according to our metrics. The integration is smooth."
"Azure Monitor is really just a source for Dynatrace. It's just collecting data and monitoring the environment and the infrastructure. It is fairly good at that."
"It's a service from Microsoft, so it will scale."
"The most valuable features of Azure Monitor are the login analytics workspace and we can write any kind of custom queries in order to receive the data that is inserted into the login analytics workspace, diagnostic settings, et cetera."
"One of the most useful aspects of this solution is the out-of-the-box functionality on all areas, especially on Application Insights, zero instrumentation, and artificial intelligence for event correlation."
"Azure Monitor is very stable."
"The solution very easily integrates with Azure services and in one click you can monitor your resource."
"A product that is well-integrated for monitoring Microsoft Azure."
"Sometimes it's more user friendly for development teams. There are some parts of Datadog that are more understandable for development teams. For example, the APM in Datadog works more manually and works like the tools in New Relic or Grafana, or Elastic. It is easier to understand for software development teams."
"The web app has a real-time support chat window in which a support engineer is chatting with you within a minute."
"Excellent autocomplete for everything in the UI."
"We can handle debugging and find out why things are breaking in our applications."
"It lets us react more quickly to things going wrong. Whereas before, it might have been 30 minutes to an hour before we noticed something going on, we will know within a minute or two if something is off, which will let us essentially get something back up and running faster for our customers, which is revenue."
"The solution has offered increased visibility via logging APM, metrics, RUM, etc."
"The ability to send notifications based on metadata from the monitor is helpful."
"Datadog has made it much easier to have a central place for people to look for logs and made it much easier to notify them of any elevated error rates or failures."
"The scalability could be improved as there are some limitations."
"We cannot use AI services with the solution."
"have used multiple products like Webex and PRTG. Some features could be added. Azure Monitor should add SMS and APIs. We have very limited access to Azure Monitor. I usually get alerts on my phone when they are integrated with Slack. I am not always available, but my team is. Sometimes, I am traveling and don't have access to my email, but I have Slack and other third-party projects that send me instant messages if a sensor goes down."
"Azure Monitor's integration with applications could be improved."
"Currently, it seems it's complicated to get the correct information in terms of what to do and how things work."
"This solution has fewer features than some of its competitors, so adding more features to it would make it better."
"The solution needs better monitoring. It requires better log controls."
"There are a lot of things that take more time to do, such as charting, alerting, and correlation of data, and things like that. Azure Monitor doesn't tell you why something happened. It just tells you that it happened. It should also have some type of AI. Environments and applications are becoming more and more complex every day with hundreds or thousands of microservices. Therefore, having to do a lot of the stuff manually takes a lot of time, and on top of that, troubleshooting issues takes a lot of time. The traditional method of troubleshooting doesn't really work for or apply to this environment we're in. So, having an AI-based system and the ability to automate deployments of your monitoring and configurations makes it much easier."
"Graph filters for logs need to be set manually which works well for JSON but not for unstructured logs."
"It could probably be a little bit of a better user experience."
"I found the solution to be stable, I did not experience any bugs or glitches. However, some of the managing team did."
"The pricing model could be simplified as it feels a bit outdated, especially when you look at the billing model of compute instances vs the containers instances."
"I'm not sure if Datadog can monitor K8s deployments in real-time. For instance, being able to see a deployment step by step visually. This would be helpful if there were any incidents during the deployment."
"The on-premise version is very difficult to upgrade."
"Deploying the agents is still very manual."
"The product needs to have more enterprise approach to configuration."
Azure Monitor is ranked 5th in Cloud Monitoring Software with 44 reviews while Datadog is ranked 1st in Cloud Monitoring Software with 137 reviews. Azure Monitor is rated 7.6, while Datadog is rated 8.6. The top reviewer of Azure Monitor writes "A powerful Kusto query language but the alerting mechanism needs improvement". On the other hand, the top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". Azure Monitor is most compared with Dynatrace, Sentry, Prometheus, Grafana and New Relic, whereas Datadog is most compared with Dynatrace, New Relic, AWS X-Ray, Elastic Observability and AppDynamics. See our Azure Monitor vs. Datadog report.
See our list of best Cloud Monitoring Software vendors and best Application Performance Monitoring (APM) and Observability vendors.
We monitor all Cloud Monitoring Software reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.