Sentry vs New Relic
Detailed comparison of Sentry and New Relic to help you choose the right monitoring tool in 2026.
Reviewed by the AI Tools Hub editorial team · Last updated February 2026
Sentry
Application error tracking and performance
Sentry provides the deepest application-level error tracking with code-level context, suspect commits, and session replay, helping developers fix bugs faster than any infrastructure-focused monitoring tool.
New Relic
Full-stack observability platform
New Relic offers the most generous free tier in observability (100GB/month, full platform access) with a unified query language that works across all telemetry types, making full-stack observability accessible without upfront commitment.
Overview
Sentry
Sentry is an application monitoring platform focused on error tracking and performance monitoring that helps developers identify, triage, and resolve software issues before they impact users. Founded in 2012 by David Cramer and Chris Jennings, Sentry started as an open-source Django error logger and evolved into a comprehensive monitoring tool used by over 100,000 organizations including Disney, Cloudflare, GitHub, and Atlassian. Unlike infrastructure-level monitoring tools like Datadog or New Relic that focus on servers and services, Sentry operates at the application code level, showing developers the exact line of code, stack trace, and user context that caused an error.
Error Tracking and Issue Management
Sentry's core strength is its error grouping and deduplication engine. When your application throws an exception, Sentry captures the full stack trace, breadcrumbs (a trail of events leading to the error), user context, browser/device information, and custom tags. It then groups similar errors into "issues" using fingerprinting algorithms, so you see one issue with 10,000 occurrences rather than 10,000 separate alerts. Each issue includes a timeline showing when it first appeared, when it regressed, and how many users it affects. The "Suspect Commits" feature links errors to specific git commits, often identifying the exact PR that introduced a bug.
Performance Monitoring and Tracing
Sentry Performance provides distributed tracing and transaction-level monitoring that shows how requests flow through your application. It measures web vitals (LCP, FID, CLS), tracks slow database queries, identifies N+1 query patterns, and highlights API endpoints with degraded response times. The "Trends" view surfaces endpoints that are getting progressively slower over time, catching performance regressions before they become user-visible. Unlike full APM tools, Sentry's performance monitoring is tightly integrated with error tracking, so you can see both errors and performance issues in the same context.
Session Replay and User Context
Session Replay records user interactions as a video-like reconstruction of their browser session, showing exactly what a user saw and did before encountering an error. This eliminates the "cannot reproduce" problem that plagues bug reports. Replays include DOM snapshots, network requests, console logs, and user clicks, all synchronized with the error timeline. Privacy controls allow masking sensitive data like form inputs and personal information. This feature bridges the gap between error monitoring and user experience tools like FullStory or LogRocket.
SDKs and Platform Coverage
Sentry supports over 100 platforms and frameworks through official SDKs: JavaScript (React, Vue, Angular, Next.js), Python (Django, Flask, FastAPI), Java, Go, Ruby, PHP, .NET, Rust, iOS (Swift, Objective-C), Android (Kotlin, Java), React Native, Flutter, and Unity. Each SDK is purpose-built for its platform, capturing platform-specific context like React component trees, Django middleware chains, or iOS crash reports with symbolicated stack traces.
Pricing and Self-Hosted Option
Sentry offers a free Developer plan with 5,000 errors and 10,000 performance transactions per month — generous enough for small projects. The Team plan starts at $26/month for 50,000 errors and 100,000 transactions. The Business plan at $80/month adds advanced features like custom dashboards, data forwarding, and extended data retention. Uniquely, Sentry is also available as a self-hosted open-source deployment using Docker Compose, though self-hosting requires significant DevOps effort and lacks some cloud-only features like Session Replay and advanced integrations.
New Relic
New Relic is a full-stack observability platform that provides monitoring across applications, infrastructure, logs, browsers, mobile apps, and serverless functions. Founded in 2008 by Lew Cirne — who previously founded Wily Technology (acquired by CA Technologies for $375 million) — New Relic was one of the earliest SaaS-based application performance monitoring (APM) tools. The company went public in 2014 and was taken private by Francisco Partners and TPG in 2023 for $6.5 billion. With over 16,000 customers including major enterprises, New Relic has reinvented itself from a traditional APM vendor into a comprehensive observability platform with a disruptive usage-based pricing model.
APM and Distributed Tracing
New Relic APM provides deep visibility into application performance across Java, .NET, Node.js, Python, Ruby, Go, and PHP. It automatically instruments popular frameworks, tracking response times, throughput, error rates, and database query performance. Distributed tracing follows requests across microservices boundaries, visualizing the full journey of a request through your architecture. The "Errors Inbox" centralizes errors from all your services into a single triage workflow, grouping similar errors and tracking their lifecycle from detection to resolution. CodeStream integration brings observability data directly into IDEs like VS Code and JetBrains, letting developers see production telemetry alongside their code.
Infrastructure and Kubernetes Monitoring
New Relic Infrastructure monitors hosts, containers, and cloud services with an agent that collects system metrics and integrates with over 500 technologies. Kubernetes cluster monitoring provides pre-built dashboards showing pod health, resource utilization, and cluster events. The Kubernetes cluster explorer visualizes namespaces, deployments, and pods in an interactive interface that makes it easy to spot resource-starved containers or failing pods. Cloud integrations pull metrics directly from AWS CloudWatch, Azure Monitor, and Google Cloud Monitoring without requiring agents on every resource.
Log Management and NRQL
New Relic's log management platform ingests logs and correlates them with traces and infrastructure metrics using "logs in context." When you view a distributed trace, you see the logs generated during that specific transaction, eliminating manual log searching. NRQL (New Relic Query Language) is a SQL-like query language that works across all telemetry types — metrics, events, logs, and traces. NRQL powers custom dashboards, alerts, and data exploration, and its familiar SQL-like syntax makes it accessible to anyone who has written a database query. This unified query language across all data types is one of New Relic's strongest differentiators.
Browser and Mobile Monitoring
New Relic Browser monitors real user experience in web applications, capturing page load times, JavaScript errors, AJAX call performance, and Core Web Vitals (LCP, FID, CLS). Session traces replay user interactions leading to errors. New Relic Mobile extends this to iOS and Android apps, tracking crashes, HTTP errors, network failures, and app launch times. Both feed into the same platform, so you can trace a user experience issue from the browser through your API gateway to the backend database query that caused the slowdown.
Pricing: The Usage-Based Model
New Relic disrupted the monitoring market in 2020 by switching to pure usage-based pricing. The free tier is genuinely useful: one full-access user, 100GB of data ingest per month, and access to the entire platform with no feature restrictions. Paid plans charge per GB of data ingested ($0.30- 0.50/GB depending on commitment) plus per full-platform user ($49-99/month). This model eliminated the per-host pricing that made competitors expensive for large fleets, but it requires careful management of data ingest volume to keep costs predictable. Teams with high-cardinality metrics or verbose logging can see ingest costs climb unexpectedly.
Pros & Cons
Sentry
Pros
- ✓ Best-in-class error grouping and deduplication — consolidates thousands of occurrences into actionable issues with suspect commits
- ✓ Generous free tier with 5,000 errors and 10,000 transactions per month, sufficient for small projects and startups
- ✓ Over 100 official SDKs covering every major language, framework, and platform with deep, idiomatic integrations
- ✓ Session Replay shows exactly what users experienced before an error, eliminating 'cannot reproduce' scenarios
- ✓ Open-source self-hosted option available for organizations that need full control over their data
- ✓ Suspect Commits and ownership rules automatically assign errors to the developer or team responsible
Cons
- ✗ Performance monitoring is less comprehensive than dedicated APM tools like Datadog or New Relic for infrastructure-level visibility
- ✗ Self-hosted deployment requires significant DevOps effort and misses cloud-only features like Session Replay
- ✗ Alert fatigue can become a problem in noisy applications — requires investment in alert rules and issue assignment workflows
- ✗ The volume-based pricing can become expensive for high-traffic applications that generate millions of events per month
- ✗ Dashboard customization is more limited compared to dedicated analytics tools — complex queries require the Discover feature
New Relic
Pros
- ✓ Generous free tier with 100GB/month data ingest and full platform access — no feature gating like competitors
- ✓ Unified query language (NRQL) works across metrics, traces, logs, and events, enabling powerful cross-telemetry analysis
- ✓ Usage-based pricing eliminates per-host costs, making it more economical for large dynamic infrastructure
- ✓ CodeStream IDE integration brings production observability data directly into VS Code and JetBrains during development
- ✓ Over 500 integrations and pre-built quickstart dashboards accelerate time to value for common technology stacks
- ✓ Logs in context automatically correlates log entries with distributed traces, eliminating manual log searching
Cons
- ✗ Data ingest costs can be unpredictable — high-cardinality metrics and verbose logging drive up bills quickly
- ✗ The platform underwent a major rewrite (New Relic One) and some older documentation references the legacy UI, causing confusion
- ✗ Per-user pricing for full platform access ($49-99/user/month) adds up for larger engineering teams
- ✗ Alert configuration is powerful but complex — setting up meaningful alerts with NRQL conditions has a steeper learning curve than threshold-based systems
- ✗ Customer support response times have been inconsistent, particularly for non-enterprise tier customers
Feature Comparison
| Feature | Sentry | New Relic |
|---|---|---|
| Error Tracking | ✓ | — |
| Performance | ✓ | — |
| Session Replay | ✓ | — |
| Profiling | ✓ | — |
| Alerts | ✓ | — |
| APM | — | ✓ |
| Infrastructure | — | ✓ |
| Logs | — | ✓ |
| Browser Monitoring | — | ✓ |
| Dashboards | — | ✓ |
Integration Comparison
Sentry Integrations
New Relic Integrations
Pricing Comparison
Sentry
Free / $26/mo Team
New Relic
Free / Pay-as-you-go
Use Case Recommendations
Best uses for Sentry
Frontend Error Monitoring for Web Applications
Frontend teams use Sentry's JavaScript SDK to capture unhandled exceptions, failed API calls, and console errors in production. Source maps provide readable stack traces even in minified production code, and Session Replay shows the exact user actions that triggered the error.
Mobile App Crash Reporting
Mobile teams use Sentry's iOS and Android SDKs to capture crashes, ANRs (Application Not Responding), and handled exceptions. Symbolicated stack traces, device context, and release health metrics help prioritize which crashes to fix first based on user impact.
Release Health and Regression Detection
Engineering teams configure Sentry to track error rates per release, automatically detecting when a new deployment introduces regressions. The Release Health dashboard shows crash-free session rates, and alerts fire when a new release degrades stability below defined thresholds.
Backend API Error Triage for Microservices
Backend teams instrument Python, Node.js, or Go services with Sentry to capture server-side exceptions with full request context. Ownership rules route errors to the responsible team automatically, and integrations with Jira or Linear create tickets directly from Sentry issues.
Best uses for New Relic
Enterprise Application Performance Management
Large engineering organizations use New Relic APM to monitor hundreds of services across Java, .NET, and Node.js stacks. Distributed tracing identifies bottlenecks across service boundaries, and service maps visualize dependencies. SLI/SLO tracking provides objective measures of reliability.
Kubernetes and Cloud-Native Observability
Platform teams use New Relic's Kubernetes integration to monitor cluster health, pod resource utilization, and deployment rollouts. The cluster explorer provides visual troubleshooting, and Pixie integration enables eBPF-based observability without code changes for deep container visibility.
Frontend Performance Optimization
Web development teams use Browser monitoring to track Core Web Vitals across real user sessions. They identify JavaScript errors affecting conversion rates, slow AJAX calls degrading user experience, and third-party scripts adding page weight. Session traces help reproduce user-reported issues.
Full-Stack Incident Investigation
SRE teams use New Relic as their single source of truth during incidents. NRQL queries correlate infrastructure metrics with application traces and logs to identify root cause. Workloads group related entities so teams can assess the blast radius of an outage across all affected services and dependencies.
Learning Curve
Sentry
Low to moderate. Installing the SDK and capturing errors requires just a few lines of code — most teams are up and running within an hour. Learning to use advanced features like custom fingerprinting, alert rules, Session Replay, and the Discover query builder takes a few days. The main ongoing effort is tuning noise: configuring which errors to ignore, setting up ownership rules, and managing alert thresholds so the team trusts Sentry notifications rather than ignoring them.
New Relic
Moderate. The New Relic One UI is well-organized, and pre-built dashboards provide immediate value for common stacks. However, getting the most out of the platform requires learning NRQL for custom queries, understanding the data ingest model to control costs, and configuring alert policies with NRQL conditions. Teams familiar with SQL will find NRQL intuitive. The biggest adjustment is shifting from per-host thinking to usage-based thinking, which requires new habits around data governance and ingest optimization.
FAQ
How is Sentry different from Datadog or New Relic?
Sentry focuses on application-level errors and developer experience, showing stack traces, suspect commits, and session replays. Datadog and New Relic focus on infrastructure and APM, monitoring servers, containers, and service-level metrics. Many teams use Sentry alongside Datadog or New Relic: Sentry for finding and fixing bugs in application code, and the APM tool for monitoring infrastructure health and system-level performance.
Is the self-hosted version of Sentry production-ready?
The self-hosted version is functional and used by many organizations, but it requires running PostgreSQL, Redis, Kafka, ClickHouse, and several Sentry services via Docker Compose. Expect to invest significant DevOps effort in maintenance, upgrades, and scaling. Self-hosted also lacks some cloud-exclusive features like Session Replay and certain integrations. Most teams start self-hosted and migrate to Sentry Cloud as their needs grow.
How does New Relic's pricing compare to Datadog?
New Relic charges per GB of data ingested plus per user, while Datadog charges per host plus per product. For large fleets with many hosts, New Relic is often cheaper because there is no per-host cost. For teams with high data volumes but few hosts, Datadog may be more economical. New Relic's free tier (100GB/month, 1 user) is significantly more generous than Datadog's (5 hosts, 1-day retention). The right choice depends on your specific infrastructure size and data volume.
What is NRQL, and do I need to learn it?
NRQL (New Relic Query Language) is a SQL-like language for querying all your telemetry data. Basic queries look like 'SELECT average(duration) FROM Transaction WHERE appName = 'MyApp' SINCE 1 hour ago'. You can use the platform without NRQL through pre-built dashboards, but custom dashboards, advanced alerts, and deep analysis all require NRQL. If you know SQL, NRQL takes a few hours to learn. It is one of New Relic's strongest features once mastered.
Which is cheaper, Sentry or New Relic?
Sentry starts at Free / $26/mo Team, while New Relic starts at Free / Pay-as-you-go. Consider which pricing model aligns better with your team size and usage patterns — per-seat pricing adds up differently than flat-rate plans.