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.
"For me, the best feature is the log analysis with Azure Monitor's Log Analytics. Without being able to analyze the logs of all the activities that affect the performance of a machine, your monitoring effectiveness will be severely limited."
"You can scale the product."
"The feature that I found most valuable in Azure Monitor is its monitoring abilities. With Azure Monitor, you are able to monitor all of your cloud resources across multiple subscriptions in one dashboard and create solution-specific alerts that can trigger an email to the team responsible for that specific solution."
"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."
"Good load and metrics gathering and very good analysis."
"The tools for logs and metrics are pretty good and easy to use."
"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."
"Azure Monitor is useful because of the useful application insights and telemetry, such as metrics and logs."
"The most useful feature is the APM."
"Most of the features in the way Datadog does monitoring are commendable and that is the reason we choose it. We did some comparisons before picking Datadog. Datadog was recommended based on the features provided."
"By moving to Datadog, we did not need to manage our own monitoring infrastructure anymore."
"I really enjoy the RUM monitoring features of Datadog. It allows us to monitor user behavior in a way we couldn't before."
"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 service catalog helped improve our organization by giving a good view of the flow for our microservices applications."
"I like that you can build out a dashboard pretty quickly. There are some things that come out of the box that you don't really need to do, which is great because they're default settings."
"It helps us better manage our logs."
"They need to work on a more hybrid deployment that will allow us to monitor local on-premise deployments and connect to different systems. I would like to see more integration."
"In my opinion, they should improve the overall user experience, especially when it comes to indexing and searching collective logs."
"When something goes down, we want the option to have automation in place to get it back up again as quickly as possible."
"Although it's not always the case, the price can sometimes get expensive. This depends on a number of factors, such as how many services you are trying to integrate with Azure Monitor and how much storage they're consuming each month (for example, how large are the log files?)."
"The default interface should be improved."
"It's really complex to retrieve or query the logs in Azure Monitor."
"Azure Monitor could improve network performance monitoring and make it more advanced."
"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."
"The parallel editing of the dashboards should not cause users to lose the work of another person."
"We have asked technical support questions, and sometimes they don't get back to us right away. Or when they do, it is not the right answer."
"The real issue with this product is cost control."
"Datadog is so feature-rich that it is often hard to onboard new folks and tough to decide where to invest time."
"The documentation leaves a lot to be desired for new users."
"They could have better log reporting."
"The sheer amount of products that are included can be overwhelming."
"There are things about it that we would like to be fixed, such as it is taking averages of average. This results in data that we don't expect."
Azure Monitor is ranked 4th in Application Performance Monitoring (APM) and Observability with 44 reviews while Datadog is ranked 1st in Application Performance Monitoring (APM) and Observability 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, Prometheus, Sentry, 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 Application Performance Monitoring (APM) and Observability vendors and best Cloud Monitoring Software vendors.
We monitor all Application Performance Monitoring (APM) and Observability 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.