S
Sentry
⚔️
D
Datadog

Sentry vs Datadog

Compare Sentry and Datadog side by side. Features, pricing, pros and cons to help you choose the right developer tool platform.

🏆 Quick Verdict

Sentry leads for application-level error tracking with developer-focused context. Datadog leads for infrastructure observability, metrics, and full-stack monitoring at scale. Many teams use both — Sentry for code errors, Datadog for infrastructure metrics.

Overall Scores

Sentry

overall 4.7/5
ease Of Use 4.5/5
design 4.5/5
features 4.8/5
value 4/5
support 4.5/5

Datadog

overall 4.6/5
ease Of Use 3.8/5
design 4.5/5
features 5/5
value 3.5/5
support 4.5/5

Feature Comparison

Sentry Advantages

  • releaseTracking
  • selfHostable

Both Have

  • = errorTracking
  • = performanceMonitoring
  • = sessionReplay
  • = alerting
  • = sourceMapSupport
  • = SDK Support
  • = dashboards
  • = apm

Datadog Advantages

  • uptime
  • logManagement

Pricing Comparison

Sentry

Free starting

  • free: Available
  • team: $26/mo
  • business: $80/mo
  • enterprise: custom

Datadog

Free starting

  • free: Available
  • pro: $15/mo
  • enterprise: custom

Pros & Cons

Sentry

Pros

  • + Best-in-class error tracking with stack traces
  • + Session replay to see what users did before errors
  • + Wide SDK support (50+ platforms)
  • + Strong open-source community
  • + Excellent developer experience

Cons

  • Can get expensive at scale
  • Free tier has limited event quota
  • Overwhelming alert noise without tuning
  • Performance monitoring add-on costs extra
Datadog

Pros

  • + Full-stack observability in one platform
  • + Best-in-class APM and distributed tracing
  • + Powerful dashboards and visualizations
  • + Extensive integrations (600+)
  • + AI-powered anomaly detection

Cons

  • Very expensive at scale
  • Complex pricing model
  • Learning curve for newcomers
  • Can be overkill for small teams

In-Depth Analysis

Sentry's core strength is error context. When an exception fires in production, Sentry captures the full stack trace, the user's browser/OS, the code version, recent breadcrumbs (what the user did before the error), and even the source-mapped code snippet. Session replay means you can watch exactly what the user saw. For developers debugging production issues, this context is invaluable.

Datadog is an observability platform in the truest sense — metrics, logs, traces, and now security signals, all unified in one place. The APM product traces requests across microservices with automatic instrumentation, the Logs product makes log aggregation and search fast, and the 600+ integrations connect Datadog to every piece of infrastructure you're likely running. For DevOps and SRE teams, Datadog is the command center.

Price comparison is stark. Sentry's free tier handles 5,000 errors/month and is genuinely usable for small projects. Their Team plan at $26/month per 100K errors is reasonable. Datadog charges per host ($15-23/month per host for Infrastructure, plus separate per-GB rates for Logs and APM). A 10-node production cluster with Datadog APM + Logs can easily run $1,000+/month.

For smaller teams with a single application, Sentry often provides 80% of the observability value at 10% of the cost. For larger engineering organizations running distributed microservices on Kubernetes, Datadog's unified observability becomes hard to replace. The 'use both' answer is common: Sentry on the code side, Datadog on the infrastructure side.

Who Should Choose What?

Choose Sentry if:

Development teams who want deep error context and session replay to debug production issues

Choose Datadog if:

DevOps and SRE teams managing distributed infrastructure who need unified metrics, logs, and traces

Ready to Get Started?

Try both platforms free and see which one feels right.