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.
"The most valuable aspect is the APM which can monitor the metrics and latencies."
"I don't have to worry about upgrades with the AWS version."
"For us to have visibility into our app stack and the hardware we run has been highly beneficial."
"It helps us better manage our logs."
"The solution allows flexibility and heightened observability for presenting data, creating indicators, and setting service-level objectives."
"The most valuable feature I have found is the elastic container service."
"The biggest thing I liked was the combination of all the things - monitoring, log aggregation, and profiling."
"Datadog's seamless integration with Slack and PagerDuty helped us to receive alerts right to the most common notification methods we use (our mobile devices and Slack)."
"The Elastic User Interface framework lets us do custom development when needed. You need to have some Javascript knowledge. We need that knowledge to develop new custom tests."
"It's easy to deploy, and it's very flexible."
"It has always been a stable solution."
"The solution has been stable in our usage."
"The tool's most valuable feature is centralized logging. Elastic Common Search helps us to search for the logs across the organization."
"Good design and easy to use once implemented."
"It is a powerful tool that allows users to collect and transform logs as needed, enabling flexible visualization and analysis."
"The solution is open-source and helps with back-end logging. It is also easy to handle."
"Lately, chat support has a longer waiting time."
"I would like testing for data in the future."
"Sometimes it’s difficult to customize certain queries to find specific things, specifically with the logging solution."
"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."
"The documentation leaves a lot to be desired for new users."
"I would love to see support for front-end and mobile applications. Right now, it is mostly all back-end stuff. Being able to do some integration with our front-end products would be awesome."
"We have recently had a number of issues with stability and delays on logging, monitoring, metric evaluation, and alerts."
"We need more visibility into the error tracking dashboard."
"Elastic Observability is reactive rather than proactive. It should act as an ITSM tool and be able to create tickets and alerts on Jira."
"In the future, Elastic APM needs a portfolio iTool. They can provide an easy way to develop the custom UI for Kibana."
"Improving code insight related to infrastructure and network, particularly focusing on aspects such as firewalls, switches, routers, and testing would be beneficial."
"Elastic Observability needs to have better standardization, logging, and schema."
"The price is the only issue in the solution. It can be made better and cheaper."
"Elastic APM's visualization is not that great compared to other tools. It's number of metrics is very low."
"If we had some pre-defined templates for observability that we could start using right away after deploying it – instead of having to build or to change some of the dashboards – that would be helpful."
"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."
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.