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.
"It has provided visibility with ease of implementation and allowed multiple teams to quickly onboard it."
"Its integration is most valuable because you can integrate it with various service providers such as AWS, .Net, etc."
"The most valuable features have been: Sharable dashboards, TimeBoards, dogstatsd API, Slack Integration, Event logging API. CloudTrail Events, Tags, alerts, and anomaly detection. EBS Volume Snapshot Age, which they added upon request."
"The seamless integration between Datadog and hundreds of apps makes onboarding new products and teams a breeze."
"It is easy to implement and scale applications with standardized visibility, monitoring and alerting"
"We integrate our application logs. It is great to be able to tie our metrics and our traces together."
"The solution has offered increased visibility via logging APM, metrics, RUM, etc."
"The ease of correcting these dashboards and widgets when needed is amazing."
"Dynatrace provide us the in-depth details to know what is wrong in the application and what are performance issues, then really quickly we are able to debug any performance issues or any other performance-related issues."
"The proactive monitoring that we can do with Dynatrace where it is 24/7 on with all the user experience indexed and everything coming into us."
"We can see each session, end-to-end, and discover issues."
"I think the design is pretty scalable. It's pretty easy to add additional nodes if we need to. Also, it's easy to migrate changes from one environment to another."
"We have drastically reduced the delay taken by the diagnostic phase. As we identify the root cause very rapidly, we can now focus on the solution and communication."
"It is cleaner and more compact with good UX/UI."
"Helps us to see the troubleshooting points or what is hiccuping. This is where we go. We reboot, fix it, or do whatever it takes for it to be taken care of."
"We can see all the degradation of services in real-time, then we know exactly what the root cause of degradation is."
"Geo-data is also something very critical that we hope to see in the future."
"The way data is represented can be limiting. When I first tried it out a long time ago, you could graph a metric and another metric, and they'd overlay, but you couldn't take the ratio between the two."
"In the past two years, there have been a couple of outages."
"Datadog could always lower the price!"
"Once Datadog has gained wide adoption, it can often be overwhelming to both know and understand where to go to find answers to questions."
"I would love to see more metrics or analytics in IoT devices."
"We need more integration functionality, including certain metrics integration."
"We want to reduce having to go to different screens to obtain all the information."
"The dashboarding in Dynatrace is not very good. We have used other monitoring tools like AppDynamics. We are also using AppDynamics for some of our products. If I compare Dynatrace with those monitoring tools, the dashboarding is not as good. If I have to create a dashboard it takes me time, the experience is not that good."
"We would like the AI to produce more scientific data with less configuration."
"Filters should have a “negative” option."
"The AppMon 6.5 is problematic in configuring. It is little finicky. When we configured the JVM, it did not work."
"The scalability is there, but it is a headache when you do a lot of stuff and when you need to compare a lot of servers and do a lot of things. The scalability is very difficult to maintain."
"Network monitoring is lacking and could be improved."
"As the product is evolving quickly and product features are added on a monthly basis, a more transparent roadmap would be more than welcome."
"It would be nice if there were a way that it could be made simpler, given the complexity of the things that we're monitoring."
Datadog is ranked 1st in Application Performance Monitoring (APM) and Observability with 137 reviews while Dynatrace is ranked 2nd in Application Performance Monitoring (APM) and Observability with 341 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 Application Performance Monitoring (APM) and Observability vendors, best Log Management vendors, and best Container Monitoring 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.
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.