Datadog and Sentry compete in the realm of application monitoring and error tracking. Datadog seems to have the upper hand due to its extensive feature set and extensive integration capabilities.
Features: Datadog offers sharable dashboards, integration capabilities, and APM features. It centralizes data effectively and provides actionable insights with an extensive list of integrations. Sentry specializes in real-time error tracking, which includes rich contextual information aiding in debugging, but lacks the broader feature set of Datadog.
Room for Improvement: Datadog could improve its performance with older metrics and simplify its pricing structure, in addition to offering better dashboard control. Sentry can enhance its integration capabilities, provide more detailed documentation, and offer more granular customizations.
Ease of Deployment and Customer Service: Datadog supports deployment across private, public, and hybrid clouds with generally responsive customer support, though response times can vary. Sentry's deployment is primarily in public and private clouds and is praised for quick customer support responses.
Pricing and ROI: Datadog's pricing is complex and demands careful cost monitoring, though its extensive features provide substantial ROI through operational efficiencies. Sentry features a straightforward and cost-effective pricing model, with open-source options and flexible paid plans offering good value, particularly noted for its cost-efficiency among competitors.
It has been easy to use and configure across multiple systems, each having several environments.
In future updates, I would like to see AI features included in Datadog for monitoring AI spend and usage to make the product more versatile and appealing for the customer.
The documentation is adequate, but team members coming into a project could benefit from more guided, interactive tutorials, ideally leveraging real-world data.
There should be a clearer view of the expenses.
Integrations or single sign-on capability with Microsoft would be beneficial for securing all assets.
The setup cost for Datadog is more than $100.
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.
The technology itself is generally very useful.
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.
Sentry provides real-time error tracking which is invaluable for identifying and resolving issues quickly.
At this time, I focus on finding and fixing bugs.
Product | Market Share (%) |
---|---|
Datadog | 7.2% |
Sentry | 5.8% |
Other | 87.0% |
Company Size | Count |
---|---|
Small Business | 78 |
Midsize Enterprise | 42 |
Large Enterprise | 82 |
Company Size | Count |
---|---|
Small Business | 6 |
Midsize Enterprise | 3 |
Large Enterprise | 3 |
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.
Sentry is a robust error management system known for real-time error tracking and integration with tools like Slack, GitLab, and Jira, benefiting those seeking comprehensive application performance insights.
Sentry offers a seamless platform to monitor errors in both front-end and back-end applications, providing real-time alerts and comprehensive event log context. With its integration capabilities, teams effectively track application metrics and access performance data without direct production access, ensuring enhanced reliability. Sentry's features such as event grouping and code trace logs linked to Git repositories highlight its utility in maintaining application efficiency. Enhanced security and regular updates make it a preferred choice over competitors. Despite some requests for improvements in automation and UI enhancements, Sentry remains invaluable for error management and application performance monitoring.
What are the key features of Sentry?In industries like technology, Sentry is crucial for monitoring errors in web applications, offering real-time alerts and performance tracking. It is frequently used in ETL processes to detect failures without direct developer access, benefiting teams who manage large-scale applications and databases efficiently.
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