New Relic vs Sentry: Application Monitoring Comparison 2026

Compare New Relic and Sentry for application performance monitoring and error tracking. See pricing, features, and which tool is better for your development team.

Updated 2026-09 · 2026

New Relic

Full-stack observability platform for application performance monitoring

$99per user/month

Strengths

+Comprehensive full-stack observability across infrastructure, applications, and logs
+Advanced APM with distributed tracing and service maps
+Powerful query language (NRQL) for custom analytics

Weaknesses

-Expensive pricing that scales quickly with data ingestion
-Steep learning curve for new users
-Can be overkill for simple error tracking needs

Best for

Enterprise teams needing comprehensive observability across their entire stack with deep performance insights

Sentry

Error tracking and performance monitoring focused on developer workflow

$26per month (Team plan)

Strengths

+Excellent error tracking with detailed stack traces and context
+Developer-friendly workflow with source code integration
+Strong open-source community and self-hosting option

Weaknesses

-Less comprehensive infrastructure monitoring than New Relic
-Performance monitoring features are newer and less mature
-Limited log management capabilities

Best for

Development teams prioritizing error tracking and debugging with a focus on code-level insights

Feature Comparison

Feature	New Relic	Sentry
Free Tier	100GB data/month free	5K errors + 10K performance units/month
Error Tracking	Available with full context	Core feature with rich stack traces
APM & Performance	Advanced APM with deep insights	Performance monitoring (newer feature)
Distributed Tracing	Comprehensive tracing across services	Available with performance monitoring
Infrastructure Monitoring	Full infrastructure observability	Limited infrastructure insights
Log Management	Centralized log management included	Basic log capture, not primary focus
Real User Monitoring	Comprehensive RUM with session replay	Session replay available
Alerting	Advanced alerting with ML anomaly detection	Issue-based alerts with customizable rules
Source Code Integration	Available via integrations	Deep GitHub/GitLab integration built-in
Self-Hosting	Not available	Open-source self-hosting option
Query Language	NRQL for custom queries	Discover query interface
Mobile App Monitoring	Native iOS and Android monitoring	Mobile SDKs for error tracking

The Verdict

Choose Sentry if you're a development team focused on error tracking and debugging, especially if you're working with limited budgets—its free tier and developer-centric features are excellent. Choose New Relic if you need comprehensive full-stack observability including infrastructure, logs, and advanced APM, and have the budget for an enterprise-grade monitoring solution.

How to switch from New Relic to Sentry

Full New Relic export guide →

1Export historical data from New Relic using the Historical Data Export feature (pushes NRDB events/metrics/logs to an S3 bucket in Parquet format) or run key NRQL queries and export results as CSV for your own records — Sentry won't import this data directly.
2Create a Sentry account, set up a project per application/service, and install the appropriate Sentry SDK (JavaScript, Python, Node, etc.) alongside your existing New Relic agent so both run in parallel for a few weeks.
3Recreate your alerting rules manually in Sentry's issue-based alert system, since New Relic's ML-based anomaly alerts and NRQL alert conditions don't transfer over automatically.
4Reconnect integrations you rely on — GitHub/GitLab for source code context, Slack for notifications, and Jira for issue tracking — through Sentry's native integrations.
5Compare error and performance data between both tools during the parallel run to confirm Sentry is catching the issues you care about, then migrate dashboards or recreate key views in Sentry's Discover interface.
6Once the team is confident in Sentry's coverage, remove New Relic agents from your codebase, downgrade or cancel the New Relic subscription, and document the cutover date for reference.

New Relic vs Sentry: common questions

How do I export my data from New Relic before switching to Sentry?+

New Relic's Historical Data Export feature lets you push NRDB data (events, metrics, logs) to your own S3 bucket in Parquet format, or you can run individual NRQL queries and export the results as CSV from the query builder UI. There's no native New Relic-to-Sentry data migration path, so most teams archive the exported data for historical reference rather than importing it into Sentry.

What do I lose by moving from New Relic to Sentry?+

You lose infrastructure monitoring, centralized log management, synthetic monitoring, and NRQL-based custom analytics across non-error data. Sentry covers error tracking and performance monitoring well but isn't a full observability replacement, so many teams pair it with a separate infrastructure/log tool if they drop New Relic entirely.

Is Sentry's free tier enough for a small team?+

For a small team with low error volume (under 5K errors and 10K performance units/month), yes, the free Developer plan covers basic error tracking and performance monitoring for one user. Once you add teammates or exceed those limits, you'll need the Team plan at $26/month plus usage-based overages.

Does Sentry integrate with the same tools as New Relic?+

Sentry has strong native integrations with GitHub, GitLab, Jira, Slack, and most CI/CD pipelines, often deeper than New Relic's source code integrations. It doesn't have New Relic's breadth of cloud infrastructure integrations (AWS, Azure, Kubernetes dashboards), so you may need a separate tool if you relied on those.

How does Sentry's cost compare to New Relic over time?+

New Relic's per-user pricing ($99/user/month for full platform users) plus data ingestion costs scales quickly as your team and data volume grow. Sentry's Team plan starts at $26/month with usage-based pricing for errors and performance units, which is generally cheaper for small-to-mid teams focused mainly on error tracking rather than full-stack observability.