Elastic APM

Management (CSPM) (7th)Ranking in Application Performance Monitoring (APM) and Observability7thRanking in IT Infrastructure Monitoring8thRanking in Log Management15thRanking in Container Monitoring4thRanking in Cloud Monitoring Software7thRanking in other categoriesNo ranking in other categoriesMindshare comparisonAs of March 2025, in the Application Performance Monitoring (APM) and Observability category, the mindshare of Datadog is 8.9%, down from 11.5% compared to the previous year. The mindshare of Elastic Observability is 5.6%, down from 5.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.Application Performance Monitoring (APM) and ObservabilityFeatured ReviewsUse our free recommendation engine to learn which Application Performance Monitoring (APM) and Observability solutions are best for your needs.841,605 professionals have used our research since 2012.Top IndustriesCompany SizeQuestions from the CommunityComparisonsProduct ReportsOverviewSample Customers Find out what your peers are saying about Datadog vs. Elastic Observability and other solutions. Updated: February 2025.841,605 professionals have used our research since 2012.See our Datadog vs. Elastic Observability report. 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.

HomeDatadog vs. Elastic ObservabilityDatadog and Elastic are both solutions in the Application Performance Monitoring (APM) and Observability category. Datadog is ranked #1 with an average rating of 8.7, while Elastic is ranked #7 with an average rating of 8.1. Datadog holds a 8.9% mindshare in APM, compared to Elastic’s 5.6% mindshare. Additionally, 97% of Datadog users are willing to recommend the solution, compared to 88% of Elastic users who would recommend it. Comparison Buyer's GuideExecutive SummaryUpdated on Jan 5, 2025Datadog and Elastic Observability compete in the monitoring and observability category. Datadog seems to have the upper hand with its ease of use and strong integration capabilities, whereas Elastic Observability stands out for its customization and cost-effectiveness.Features: Datadog's remarkable features include sharable dashboards, robust integration with services like AWS and Docker, and extensive visualization tools for comprehensive monitoring. Elastic Observability excels in analytics and search functionality, offering a highly customizable platform that integrates well with various data sources and monitoring systems.Room for Improvement: Datadog users often encounter challenges with the complexity of customizing dashboards and managing high costs, especially for logs and APM features. They also seek more advanced integrations and improved documentation. Elastic Observability faces criticism for its steep learning curve and lacks more automated features, predictive analytics, and proactive alerting capabilities, which users hope will improve to enhance scalability.Ease of Deployment and Customer Service: Datadog offers flexible deployment across multiple cloud environments, making it adaptable but potentially complex. Its customer service is generally helpful and responsive, although inconsistency and delays are noted. Elastic Observability is commonly deployed on-premises, providing strong data control but increasing setup complexity. Its support is seen as high-quality but could improve in timeliness.Pricing and ROI: Datadog's pricing, perceived as higher due to usage-based billing, can lead to unexpected costs. It provides a reasonable ROI with comprehensive monitoring capabilities, though cost management remains a concern. Elastic Observability is viewed as more cost-effective, particularly for larger deployments, thanks to its open-source model that offers flexibility and savings. However, close management of its licensing is crucial to avoid potential high costs.To learn more, read our detailed Datadog vs. Elastic Observability Report (Updated: February 2025).Review summaries and opinionsROICustomer ServiceScalability IssuesStability IssuesRoom For ImprovementSetup CostSUValuable FeaturesCategories and RankingRanking in Application Performance Monitoring (APM) and Observability1stRanking in IT Infrastructure Monitoring2ndRanking in Log Management3rdRanking in Container Monitoring2ndRanking in Cloud Monitoring Software1stRanking in other categoriesNetwork Monitoring Software (3rd), AIOps (1st), Cloud Security Posture

Scripts are enabled for packages, raygun-apm will inspect your project's dependencies and warn you if a version of a dependency is known to be incompatible.Please let us know if there's another database adapter or library you'd like supported.Cloud Providersraygun-apm can be used with a number of cloud providers.Dockerraygun-apm can be used with Docker-based deployments. Please see the APM Agent Docker setup guide for information on installing the agent.If the agent is running in a separate container to the Node application, you will need to set the RAYGUN_AGENT_HOST to the hostname of the agent's container.When using docker-compose, hostnames are automatically created for each container, using the name of the service.For example, if our APM Agent service was named raygun, as in the above example, our node application would need to have the environment variable RAYGUN_AGENT_HOST=raygun.Herokuraygun-apm provides support for Heroku via a custom buildpack that will install and run the APM agent alongside your application.For more information, see the Heroku Buildpack guide on Raygun's documentation site.AWS Elastic Beanstalkraygun-apm provides support for AWS Elastic Beanstalk, using the .ebextensions system to install and run the APM Agent. Please see the setup guide on the Raygun documentation site for more detail.Azure App Servicesraygun-apm provides support for Azure App Services, using Azure Extensions to install and run the APM agent. Please see the APM Agent setup guide for Azure on the Raygun documentation site for instructions on installing the agent.Performanceraygun-apm introduces a performance overhead to your application, due to the use of V8's CPU profiler and the Node async_hooks module to capture APM information. As such, using raygun-apm in production can cause noticeable slowdown to application code.This is similar to how a web application behaves when capturing a CPU profile in Chrome. Our current benchmarks suggest this overhead is currently around 30% at worst, although we're