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.
"Datadog provides tracing and logging, whereas Dynatrace focuses on tracing, and Splunk is more of a logging tool. Datadog's advantage is that we don't need two tools."
"It has scaled great. I haven't run into any problems anywhere that I've used it. They have handled everything that we have needed them to."
"The visibility into our network has allowed for quick diagnosis of failures, identification of underutilized or over-utilized resources, and allowed for cloud cost optimization opportunities."
"Datadog helps us detect issues early on and helps in troubleshooting."
"The dashboards are great."
"It has turned into an operational dashboard. If you felt something is going wrong, you can immediately open up Datadog. It has been our go to application because we know the answer will be there."
"Datadog's log aggregation is really helpful since it lets me and every other engineer on my team login, view, and share logs when we need to debug our application."
"We have been able to set very specific CPU and memory alerts, at the very base level, then we started to pull real business value, like 99th percentile response rates for our API calls."
"The real user experience monitoring is very helpful. We can see what real users are seeing, what JavaScript errors, what pages are very slow for them. As well, it helps to correlate the front-end users to the back-end application components, and the corresponding Method which is failing, as well. We are able to go to the correct spot and fix the issue."
"It scales well. We are going to be able to use it for everything we need. "
"Automatic instrumentation of new services and technology without the need to install specific agents or modules."
"It gives more visibility into all the coding (the black screen). It gives a nice screen. You can see ups and downs. You can see where the traffic is getting impacted, more on the convergence side."
"They have quick answers for scalability."
"The way it shows a problem on the dashboard is pretty good."
"The User experience monitor is a real added value."
"Provides bespoke dashboards and reports which help our business to grow."
"ECS could be improved by including more tutorials for beginners to reduce the barriers to entry."
"I'd like to see better pricing and more integration in the next release."
"The pricing should be less of a surprise."
"Some of the interface is still confusing to use."
"It can have an artificial intelligence component. Even though I can seamlessly look at end-to-end security, it would be better to have alerts and notifications powered by an AI engine. I am not sure if they have an AI component. We have not reached out to them or looked at it, but this is something that I keep on talking about within our company in terms of features. Such a feature would be good to have, and it would further optimize my Security Ops team's abilities."
"As a new customer, the Datadog user interface is a bit daunting."
"I find the training great. That said, it is set for the LCD (lowest common denominator). Of course, this is very helpful to sell the product, yet, to really utilize the product, you need to get more detailed."
"They need to implement template variables into the message response body."
"We found it was quite challenging in terms of the learning curve."
"The other feature that Dynatrace should have is - from what I see in Dynatrace in our PoC - when you auto-upgrade the agents, the JVM or the application has to be restarted. But if you have something like an "auto-attach" feature, to attach the agent for the running process, it would not require a JVM restart. That would be nicer. That is a killer point."
"It would be great to have Synthetic automatically retrieve what the customer sees on his side."
"If you want to see a month's data, it keeps on spinning. Here is an improvement which needs to happen, which is the case with all applications or tools. There is a lot of data, and either we have to change the way we are logging or the application needs to be enhanced."
"Training is required for all of the people who will be using it, and this should not be overlooked. I would even recommend nominating an SME in each of the three areas covered: user behaviour analysis, development, and infrastructure/operations support."
"I need more experience."
"I do know that for the size of our organization, we're talking thousands of agents and hundreds of applications, it does get to the point where the servers themselves that house Dynatrace are at a point where, in some cases, they are just too big for one machine, since you have to have an entire application ecosystem all funnel into a single system."
"We have had problems with our middle layer application implementation."
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.