Datadog and Elastic Observability are leading solutions in the observability market. Datadog has the upper hand in ease of use and comprehensive metrics, whereas Elastic Observability is noted for its flexibility and open-source nature.
Features: Datadog users value its detailed metrics, integrations, and cloud-native capabilities. Elastic Observability users recognize its powerful search capabilities and analytics flexibility thanks to Elasticsearch. Datadog is known for out-of-the-box usability, while Elastic is preferred for custom solutions.
Room for Improvement: Datadog users suggest the need for more flexible dashboards and reduced cost for advanced features. Elastic Observability users desire better documentation and a simpler initial setup. Datadog needs to address cost issues, whereas Elastic could improve user onboarding with better guides.
Ease of Deployment and Customer Service: Datadog reviewers highlight a straightforward deployment process and responsive customer support. Elastic Observability reviewers mention a steeper learning curve and mixed feedback on support responsiveness. Datadog offers an easier start and efficient service, while Elastic provides more complex setup options with variable support.
Pricing and ROI: Users indicate Datadog has a higher initial setup cost but also acknowledge its rich feature set justifies the price. Elastic Observability, being open-source, offers a lower upfront cost but might incur additional expenses with complex deployments. Datadog provides clear value for investment if budget allows, whereas Elastic offers cost benefits with potential long-term customization and growth.
One example is the inability to monitor very old databases with the newest version.
Elastic Observability could improve asset discovery as the current requirement to push the agent is not ideal.
Elastic Observability seems to have a good scale-out capability.
What is not scalable for us is not on Elastic's side.
The license is reasonably priced, however, the VMs where we host the solution are extremely expensive, making the overall cost in the public cloud high.
Elastic Observability is cost-efficient and provides all features in the enterprise license without asset-based licensing.
It is very stable, and I would rate it ten out of ten based on my interaction with it.
Elastic Observability is really stable.
The most valuable feature is the integrated platform that allows customers to start from observability and expand into other areas like security, EDR solutions, etc.
All the features that we use, such as monitoring, dashboarding, reporting, the possibility of alerting, and the way we index the data, are important.
Datadog is a comprehensive cloud monitoring platform designed to track performance, availability, and log aggregation for cloud resources like AWS, ECS, and Kubernetes. It offers robust tools for creating dashboards, observing user behavior, alerting, telemetry, security monitoring, and synthetic testing.
Datadog supports full observability across cloud providers and environments, enabling troubleshooting, error detection, and performance analysis to maintain system reliability. It offers detailed visualization of servers, integrates seamlessly with cloud providers like AWS, and provides powerful out-of-the-box dashboards and log analytics. Despite its strengths, users often note the need for better integration with other solutions and improved application-level insights. Common challenges include a complex pricing model, setup difficulties, and navigation issues. Users frequently mention the need for clearer documentation, faster loading times, enhanced error traceability, and better log management.
What are the key features of Datadog?
What benefits and ROI should users look for in reviews?
Datadog is implemented across different industries, from tech companies monitoring cloud applications to finance sectors ensuring transactional systems' performance. E-commerce platforms use Datadog to track and visualize user behavior and system health, while healthcare organizations utilize it for maintaining secure, compliant environments. Every implementation assists teams in customizing monitoring solutions specific to their industry's requirements.
Elastic Observability is primarily used for monitoring login events, application performance, and infrastructure, supporting significant data volumes through features like log aggregation, centralized logging, and system metric analysis.
Elastic Observability employs Elastic APM for performance and latency analysis, significantly aiding business KPIs and technical stability. It is popular among users for system and server monitoring, capacity planning, cyber security, and managing data pipelines. With the integration of Kibana, it offers robust visualization, reporting, and incident response capabilities through rapid log searches while supporting machine learning and hybrid cloud environments.
What are Elastic Observability's key features?Companies in technology, finance, healthcare, and other industries implement Elastic Observability for tailored monitoring solutions. They find its integration with existing systems useful for maintaining operation efficiency and security, particularly valuing the visualization capabilities through Kibana to monitor KPIs and improve incident response times.
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.