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.
"The most valuable aspect is the APM which can monitor the metrics and latencies."
"The RUM solution has improved our ability to triage faster and hand more capabilities to our customer support."
"We like the distributed tracing and flame graphs for debugging. This has been invaluable for us during periods of high traffic or red alert conditions."
"Datadog is providing efficiency in the products we develop for the wireless device engineering department."
"Integrating Datadog with other platforms has made our monitoring processes a bit easier. It's not super simple, but it's manageable."
"Flame graphs are pretty useful for understanding how GraphQL resolves our federated queries when it comes to identifying slow points in our requests. In our microservice environment with 170 services."
"The most valuable features are the dashboards and the reporting."
"Datadog has proven to be easy to set up and legible for both development and operational teams."
"We can report and monitor on specific use cases which could not be monitored with SAP or other tooling."
"With Dynatrace, we have synthetic checks and real-user monitoring of all of our websites, places where members and providers can interact with us over the web. We monitor the response times of those with Dynatrace, and it's all integrated into one place."
"I am primarily doing DC RUM, so on that side there are a lot of awesome abilities where people who can't implement an agent are able to still monitor a lot of their apps and decodes."
"Once you are trained on the solution, it's easy to navigate. It's got very good documentation and training offerings."
"Scalability is outstanding. It won't tax our environment at all as it will scale sideways."
"The most valuable features are ease of deployment, UI, and collected data. Its deployment is really easy. In just a few hours, you can have a very good outcome, and you can see everything, which is very valuable. It collects a good amount of data."
"It collects and analyses information with AI, which is useful."
"It gives complete stats of the user and what they are doing."
"There is always room for improvement when dealing with cloud-based technologies. Mainly, I would say, it's just increasing our offerings to attract various other types of industries and businesses across more fields."
"One area where I was really looking for improvement was the CSPM product line. I had really wanted to have team-level visibility for findings, since the team managing the resources has much more context and ability to resolve the issue, as the service owner. However, this has been added to the announcement in a recent keynote."
"The parallel editing of the dashboards should not cause users to lose the work of another person."
"Datadog has a lot of features kind of cramped into one dashboard. It's quite hard to get around what feature does exactly what. There was a steep learning curve, trying to navigate through menus."
"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."
"Geo-data is also something very critical that we hope to see in the future."
"While I like the ease of use, when compared with Tenable Nessus they could still improve their usability."
"We have recently had a number of issues with stability and delays on logging, monitoring, metric evaluation, and alerts."
"The web version of the client interface needs more features that are in the Java-based thick client."
"More visibility into Python processes."
"The only challenge is that it's an extensive tool that requires a significant amount of time to learn."
"Add support for Ruby."
"I would say that this solution's reports are lacking a little bit, and because of this, you have to rely on API to fetch and pull data. I think they could have done a bit of a better job by providing a more user-friendly search from a reporting perspective."
"It is necessary to improve the integration with the product, Oracle Siebel."
"The pricing of the product could be improved."
"Need better mapping to true business service rather than purely technical 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.