We performed a comparison between Datadog and Elastic Observability based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Features: Datadog offers a range of valuable features, such as customizable dashboards and detailed reporting. It also excels in error reporting and log centralization, making it easier to identify and address issues. The platform's ease of use and simple setup process are appreciated by users. Performance monitoring and infrastructure monitoring are reliable, and the platform offers flexibility and additional features. Elastic Observability is known for its cost-effectiveness and favorable licensing. The comprehensive features and easy deployment and flexibility are key strengths, and the platform's machine learning capabilities are appreciated. Elastic Observability offers stable performance and has a well-designed interface. Datadog could enhance its usability, integration, learning curve, external website monitoring, and SSL security. Elastic Observability, meanwhile, requires improvements in auto-discovery, visualization, metrics, and role-based access control.
Service and Support: Some users have found the support provided by Datadog to be helpful and responsive, while others have experienced slow or unresponsive support. Elastic Observability's customer service has been highly praised for its excellent technical support and quick responses. Some customers even have a dedicated resource for their issues.
Ease of Deployment: Users generally findDatadog's initial setup to be simple and uncomplicated, with support readily accessible. The setup process for Elastic Observability varies in difficulty. While it is deemed straightforward for Docker installation, some users encounter difficulties due to various cluster configurations and distributed solutions.
Pricing: Datadog's setup cost is mixed in terms of its affordability. The pricing model is unclear and lacks documentation. Elastic Observability provides various pricing options, including a self-managed license with three tiers. It incorporates embedded or open-source components, potentially making it more economical.
ROI: Users have reported various benefits from using Datadog, including time savings and faster debugging. Elastic Observability has been found to be cost-effective, helping to reduce incidents and identify issues effectively.
Comparison Results: Elastic Observability is praised for its cost-effectiveness, favorable licensing, comprehensive features, easy deployment, and customization flexibility. Users highly value its machine learning capabilities and stable performance, making it the preferred solution.
"I find the greatest feature is being able to search across logs from various microservices."
"Datadog has so far been a breeze to use and set up."
"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 CCM, Workflows, Logs, APM, and RUM are all useful aspects of the solution."
"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."
"If we have a large load for users using our basic Datadog, it will immediately fire off an alert notifying us either something's wrong or not."
"It has a high-level insight into the infrastructure model of the application and provides important detailed data on the host and metrics, which is the main concern of our customers."
"We find they have a very helpful alert system."
"The price is very less expensive compared to the other solutions."
"Elastic APM has plenty of features, such as the Elastic server for Kibana and many additional plugins. It's a comprehensive tool when used as a logging platform."
"It has always been a stable solution."
"The solution has been stable in our usage."
"For full stack observability, Elastic is the best tool compared with any other tool ."
"The product has connectors to many services."
"I have built a mini business intelligence system based on Elastic Observability."
"We can view and connect different sources to the dashboard using it."
"I think better access to their engineers when we have a problem could be better."
"Datadog could always lower the price!"
"Once agents are connected to the Datadog portal, we should be able to upgrade them quickly."
"The setup was a bit complex."
"Federated views for Datadog dashboards are critical as large companies utilize multiple instances of the product and cannot link the metrics or correlate the metrics together. This stunts the usage of Datadog."
"Datadog isn't as mature as some of the established players like Dynatrace or Splunk. It's a new product, so they are constantly releasing new features, and I don't have much to complain about."
"We would like to see smaller or shorter tutorials and video sessions."
"I've found that the documentation is lacking in certain regards."
"Elastic Observability needs to have better standardization, logging, and schema."
"Elastic Observability is difficult to use. There are only three options for customization but this can be difficult for our use case. We do not have other options to choose the metrics shown, such as CPU or memory usage."
"The solution would be better if it was capable of more automation, especially in a monitoring capacity or for the response to abnormalities."
"The auto-discovery isn't nearly as good. That's a big portion of it. When you drop the agent onto the JVM and you're trying to figure things out, having to go through and manually do all that is cumbersome."
"Elastic APM's visualization is not that great compared to other tools. It's number of metrics is very low."
"In the future, Elastic APM needs a portfolio iTool. They can provide an easy way to develop the custom UI for Kibana."
"The price is the only issue in the solution. It can be made better and cheaper."
"Elastic Observability is reactive rather than proactive. It should act as an ITSM tool and be able to create tickets and alerts on Jira."
Datadog is ranked 1st in Application Performance Monitoring (APM) and Observability with 137 reviews while Elastic Observability is ranked 7th in Application Performance Monitoring (APM) and Observability with 22 reviews. Datadog is rated 8.6, while Elastic Observability is rated 7.8. The top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". On the other hand, the top reviewer of Elastic Observability writes "The user interface framework lets us do custom development when needed. ". Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and AppDynamics, whereas Elastic Observability is most compared with Dynatrace, New Relic, AppDynamics, Azure Monitor and Sentry. See our Datadog vs. Elastic Observability report.
See our list of best Application Performance Monitoring (APM) and Observability vendors, best IT Infrastructure Monitoring vendors, and best Log Management 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.