Find out in this report how the two Application Performance Monitoring (APM) and Observability solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
Product | Market Share (%) |
---|---|
Sentry | 5.8% |
Mezmo | 0.3% |
Other | 93.9% |
Company Size | Count |
---|---|
Small Business | 7 |
Midsize Enterprise | 3 |
Large Enterprise | 3 |
Today’s enterprises must manage a massive amount of machine data. They require a platform that enables engineering teams to deliberately route and store structured and unstructured data for different teams with unique use cases. Legacy platforms weren’t made for this moment.
Mezmo, formerly LogDNA, lets organizations ingest, process, route, analyze, and store all of their log data. Purpose-built for modern engineering teams—including developers, SREs, IT Operations, and Security Engineers—the Mezmo platform is trusted by thousands of companies for SaaS, cloud, and hybrid applications.
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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