

Datadog and Sentry are two leading products in the field of monitoring and performance management. Datadog holds an edge with its broad integration capabilities, while Sentry shines in error tracking and quick debugging.
Features: Datadog offers comprehensive monitoring with sharable dashboards, intuitive tagging, and a wealth of integrations, particularly for AWS and Docker. It is strong in anomaly detection and metrics visualization. Sentry is highly effective for real-time error tracking and performance monitoring, providing insights into application metrics and errors, which aids in quick debugging.
Room for Improvement: Datadog could benefit from more flexible dashboards and improved cost predictability. Its pricing model is often seen as complex. Sentry could enhance its integration capabilities and improve its documentation. Users also suggest better metrics customization and enhanced tracing capabilities.
Ease of Deployment and Customer Service: Datadog supports public, private, and hybrid cloud deployments, known for responsive customer service, although some variability in quality exists. Sentry is typically used in public and on-premises settings, with excellent support praised for its promptness and efficiency, facilitating quick onboarding.
Pricing and ROI: Datadog's pricing scales with usage and, while seen as high, it is justified by its features, offering significant ROI through improved efficiency. Sentry offers affordable pricing, appealing to smaller firms with open-source options, and paid plans as needed, though some feature enhancements could further improve ROI.
Previously we had thirteen contractors doing the monitoring for us, which is now reduced to only five.
Datadog has delivered more than its value through reduced downtime, faster recovery, and infrastructure optimization.
We have also seen fewer escalations for minor issues because alerts help us catch problems earlier, which indirectly reduces downtime and improves overall efficiency.
When I have additional questions, the ticket is updated with actual recommendations or suggestions pointing me in the correct direction.
Overall, the entire Datadog comprehensive experience of support, onboarding, getting everything in there, and having a good line of feedback has been exceptional.
I've had a couple instances where I reached out to Datadog's support team, and they have been really super helpful and very kind, even reaching back out after resolving my issues to check if everything's going well.
We have not contacted their technical support because everything is easy to set up under Sentry.
Datadog's scalability has been great as it has been able to grow with our needs.
Since it is a SaaS platform, we did not have to worry about backend scaling.
We have not faced any major performance issues from the platform side; it handles increased metrics and monitoring loads smoothly.
It has been easy to use and configure across multiple systems, each having several environments.
Metrics collection and alerting have been consistent in day-to-day use.
Datadog is very stable, as there hasn't been any downtime or issues since I've been here, and it's always on time.
Datadog seems stable in my experience without any downtime or reliability issues.
It would be great to see stronger AI-driven anomaly detection and predictive analytics to help identify potential issues before they impact performance.
We want to be able to customize the cost part, and we would appreciate more granular access control.
Having more transparent and granular cost control features would make it easier to manage usage.
Integrations or single sign-on capability with Microsoft would be beneficial for securing all assets.
The setup cost for Datadog is more than $100.
Pricing is mainly based on data ingestion, such as logs, metrics, and traces, and it can increase quickly if everything is enabled by default.
Everybody wants the agent installed, but we only have so many dollars to spread across, so it's been difficult for me to prioritize who will benefit from Datadog at this time.
Compared to New Relic, it provides the necessary features at a cheaper cost, especially since we moved infrastructure monitoring to Azure.
Our architecture is written in several languages, and one area where Datadog particularly shines is in providing first-class support for a multitude of programming languages.
Having all that associated analytics helps me in troubleshooting by not having to bounce around to other tools, which saves me a lot of time.
Datadog was able to find the alerts and trigger to notify our team in a very prompt manner before it got worse, allowing us to promptly adjust and remediate the situation in time.
Real-time error tracking helps our Quality Assurance team easily identify the root causes of problems or bugs and promptly inform the developers about specific issues.
At this time, I focus on finding and fixing bugs.
Sentry provides real-time error tracking which is invaluable for identifying and resolving issues quickly.
| Product | Mindshare (%) |
|---|---|
| Datadog | 4.1% |
| Sentry | 1.4% |
| Other | 94.5% |

| Company Size | Count |
|---|---|
| Small Business | 81 |
| Midsize Enterprise | 50 |
| Large Enterprise | 100 |
| Company Size | Count |
|---|---|
| Small Business | 7 |
| Midsize Enterprise | 3 |
| Large Enterprise | 3 |
Datadog offers a comprehensive platform for monitoring applications and infrastructure, providing insights into real-time metrics and optimizing performance with extensive integrations and analytics capabilities.
Datadog provides a robust monitoring platform designed for applications and infrastructure tracking. With intuitive dashboards and real-time metrics visibility, it enhances operational efficiency and enables proactive incident management. The platform supports data centralization across services, reducing downtime through its monitoring capabilities. Integration with AWS, Kubernetes, and other systems aligns with performance tracking and infrastructure management, while APM and RUM features allow tracing and user behavior analytics.
What are Datadog's Key Features?Industries utilizing Datadog benefit from detailed monitoring and comprehensive analytics across multi-cloud environments. Companies in e-commerce, finance, and technology sectors implement it for end-to-end monitoring ensuring robust application performance. The platform assists in maintaining standards through integration with services like AWS and Azure, providing efficient observability and allowing proactive issue resolution.
Sentry provides developers with real-time error tracking and performance metrics, facilitating efficient monitoring and logging across front-end and back-end systems. The platform enhances error visibility without direct production access, ensuring robust data protection.
Sentry offers a comprehensive integration with Git repositories, allowing users to gain context for errors and manage performance metrics across their entire tech stack. Its user-friendly interface, coupled with features like security and session replays, aids in rapid learning and error resolution. Support for platforms like Azure Web Services and seamless integration with communication tools further enhances its functionalities. The tool is appreciated for error and performance reporting, with integrations extending to platforms such as Slack and AWS Lambda. Users, however, seek improved integration with additional tools, enhanced tracing capabilities, task automation, and better customization for event handling.
What are the key features of Sentry?Sentry finds application across industries like banking, where it's deployed to monitor application performance and manage errors both on-premises and in the cloud. Teams benefit from its ability to trace and rectify errors while preserving system reliability and ensuring controlled access to databases.
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