We compared Datadog and Dynatrace based on our users reviews in five parameters. After reading the collected data, you can find our conclusion below:
The setup process for both Datadog and Dynatrace is generally seen as simple and uncomplicated. However, Datadog might necessitate some fine-tuning or the involvement of multiple teams, whereas Dynatrace is regarded as faster and easier to implement. Additionally, Dynatrace only requires a minimal deployment and maintenance effort, usually handled by one or two individuals even in larger settings.
Datadog offers useful features like customizable displays and data analysis, error tracking and log management, developer-friendly interface, and adaptable AI and ML capabilities. In contrast, Dynatrace excels in effortless setup, automatic infrastructure identification, intelligent problem detection, session playback, and comprehensive visibility and monitoring.
- Room for Improvement
Based on the feedback, Datadog could enhance its usability, integration capabilities, user interface intuitiveness, learning curve, monitoring of external websites, SSL security, and setup complexity. In contrast, Dynatrace could improve its user interface for management functions, handling of time zones, installation process, integration with network management tools, licensing process, documentation, and network performance monitoring.
Users have differing opinions on the setup cost of Datadog, with some finding it costly while others find it reasonable in comparison to other options. However, the pricing model lacks documentation and is confusing. In contrast, Dynatrace's pricing structure is complicated and not transparent, making accurate planning difficult. Despite being generally expensive, it provides good value for the money.
Users have reported experiencing various benefits when using Datadog, including time savings and the ability to identify and address blindspots. On the other hand, customers have found Dynatrace to be highly advantageous in terms of return on investment, with cost savings and reduced downtime being key outcomes.
The customer service and support for Datadog and Dynatrace have varying feedback. Some users appreciate the promptness and helpfulness of Datadog's support team, while others have experienced slow or unresponsive support, especially in the Asia-Pacific region. In contrast, Dynatrace generally provides responsive and available customer service, although some customers have encountered slower response times. Dynatrace's support team is praised for giving valuable answers, and they have a highly regarded customer success program called Dynatrace ONE. However, there is a need for improvement in terms of response time for both platforms.
Comparison Results
When comparing Datadog and Dynatrace, Datadog is regarded as simpler to set up and provides more flexibility and extra features. Users appreciate its dashboards, error reporting, user-friendliness, and the wide range of integrations it offers. On the other hand, Dynatrace is praised for its effortless deployment and automatic infrastructure detection, as well as its AI engine and visualization capabilities. However, users mention that improvements could be made to Dynatrace's user interface, licensing process, and documentation. Pricing and ROI experiences vary among users for both products, and customer service and support are generally satisfactory, with some room for enhancement.
"Going from viewing a metric to creating a monitor alerting on a metric is very easy."
"The most valuable aspects of the product include the APM and profiler."
"They have a very good foundation in capturing metrics, logs, and traces. It's a very nice tool for that and it allows you to apply these monitoring tools in almost any technology."
"The dashboards and the performance of the software have been great."
"We have way more observability than what we had before - on the application and the overall system."
"Datadog documentation on web pages has improved a lot and is pretty easy to follow and find."
"I have found the logging and tracing features the most valuable."
"We integrate our application logs. It is great to be able to tie our metrics and our traces together."
"Reduces the amount of knowledge that is needed by applications consuming this data."
"Helps in managing capacity planning, services performance, and tuning database performance and optimizing queries."
"Scalability is great. My biggest concern when we first put it in was the resources that it would take up, network traffic that it might create. But it seems perfectly scalable to any environment. Even on some of our heaviest use servers, it doesn't seem to affect anything."
"We use it, in many instances, to find the root cause in production."
"A feature that's one of the highlights of Dynatrace is the AI. The second most valuable feature is OneAgent. Between infrastructures, applications, operating systems, you can deploy with just a single agent and can practically install and forget about it."
"We use Dynatrace to help us understand how applications perform in different platforms."
"The Dashboard is very useful, as you can monitor different parameters on the same screen."
"It reduces our efforts to identify services failing in production."
"It is very difficult to make the solutions fit perfectly for large organizations, especially in terms of high cardinality objects and multi-tenancy, where the data needs to be rolled up to a summarized level while maintaining its individual data granularity and identifiers."
"The product needs a better Datadog agent installation."
"Even though it is powerful on its own, the UI-based design lacks elegance, efficiency, and complexity."
"I would love to see more metrics or analytics in IoT devices."
"We would like to see some versioning system for the Synthetic Tests so that we could have a backup of our tests since they are time-consuming to make and very easy to damage in a moment of error."
"The ease of implementation needs improvement."
"The setup was a bit complex."
"To be very fair, I haven't had enough experience with Datadog to pick out improvements."
"There was complexity to AppMon and getting everything set, but more specifically getting the dashboard setup."
"The container platform could include more value-added features."
"Right now, for AppMon, the maximum handling load, the transaction per minute, is around 6,500. We had an issue on Black Friday or Cyber Monday, some kind of stability issue for users who could not log in. I want to see an increase in the load, at least to 7,000 or 8,000 transactions per second"
"The configuration of the alerts, that's been a challenge in AppMon for me, right now. Some of the alerts are too noisy, but that might be my lack of some configuration."
"We ran into a problem where the Dynatrace JavaScript agent is returning errors, and it's very apparent that there's a problem. However, the customer support will ask us for seemingly unnecessary details instead of looking at our dashboard through their account to see what the problem is. They ask us for a lot of details not really related to solving the problem. As a result, we still have a few issues that were never resolved. They're not major issues, but they're kind of frustrating."
"This solution could be improved with better compatibility with legacy applications."
"They seriously have to improve their Web UI dashboard configuration and SSL timeouts. Their Web UI dashboards are very slow."
"Session export for offline analysis, like it was in AppMon, would be also nice."
Datadog is ranked 1st in AIOps with 137 reviews while Dynatrace is ranked 2nd in AIOps with 340 reviews. Datadog is rated 8.6, while Dynatrace is rated 8.8. The top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". On the other hand, the top reviewer of Dynatrace writes "AI identifies all the components of a response-time issue or failure, hugely benefiting our triage efforts". Datadog is most compared with Azure Monitor, New Relic, AWS X-Ray, Elastic Observability and AppDynamics, whereas Dynatrace is most compared with New Relic, AppDynamics, Splunk Enterprise Security, Azure Monitor and Elastic Observability. See our Datadog vs. Dynatrace report.
See our list of best Log Management vendors, best Container Monitoring vendors, and best AIOps vendors.
We monitor all AIOps 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.
We also selected Dynatrace but for different reasons.
We were looking for a solution that integrated user experience to backend systems. The RUM data captured by Dynatrace and integration to the transaction trace is phenomenal.
Datadog was lacking in the APM space when we evaluated and was very limited specifically in real user monitoring.
I've seen an early preview of Dyantrace's latest logging capabilities and can say I'm very excited, to say the least. The solution is automated and traced. For a comprehensive solution to improve observability and reduce outage times we are very happy with Dynatrace.
Our organization ran comparison tests to determine whether the Datadog or Dynatrace network monitoring software was the better fit for us. We decided to go with Dynatrace. Dynatrace offers network monitoring capabilities that take into account their users’ need for the most in-depth and accurate information and solutions. It offers analysis powered by a cutting-edge and fully automated AI. This artificial intelligence is designed to spot in real time any issue that might appear in the network on both the code and the infrastructure levels. Network administrators will be offered an in-depth analysis of the issue. The report will show the nature of the problem, where in the network it can be located, and potential solutions that can be implemented. Dynatrace’s real-time reporting significantly cuts down the response time of administrators to issues.
Datadog’s network monitoring software does not offer AI reporting or analysis. While it does offer features that enable users to track issues in their networks, it does not offer anything that is as robust and in-depth as Dynatrace’s fully automated AI. Administrators have to go and constantly monitor the network for issues instead of receiving automatic notifications that can direct them to the problems at hand.
Dynatrace’s dashboards can take the data that the AI collects and lay it out for the administrative or executive teams in clear ways. It is easy to customize these dashboards according to what you need. In fact, the creation of dashboards is now automated. You tell the software what you want to see and it will build the dashboard for you.
Datadog offers dashboards that provide near real-time visibility. They track the health of the network applications and provide indicators of the network’s overall condition. These dashboards are somewhat easy to create. However, they lack the automation that Dynatrace provides.
Conclusion
While Datadog offers a solution that can provide effective network monitoring, Dynatrace’s features make it a better option. Its AI and automation make it a far more effective product.