Sentry vs Datadog
A side-by-side comparison from 135 GitHub-verified developers who shipped production code on both platforms.
Sentry wins on developer-first error tracking and pricing; Datadog wins on breadth (APM, infra, logs, security in one platform). Most teams run both — Sentry for code, Datadog for infrastructure.
Benchmark Comparison
| Metric | Sentry | Datadog |
|---|---|---|
| Error tracking quality | Best-in-class | Functional |
| Infrastructure metrics | No | Best-in-class |
| APM tracing | Strong (2024+) | Mature |
| Logs | Newer product | Mature |
| Pricing predictability | Per-error tiers | Opaque |
| Session Replay | Yes | Via RUM |
| Release tracking | First-class | Yes |
| Alert fatigue defaults | Low | Higher |
Operational Verdicts
Sentry tells you what broke and who broke it. Stack traces are useful, alerts route to the engineer who shipped the regression. Datadog's error tracking exists but isn't the product's focus.
Datadog covers infra metrics, APM, logs, RUM, security. The pane-of-glass story is real. For ops-heavy teams that need infrastructure visibility, Datadog's breadth justifies the price.
Sentry's tiers are easy to forecast. Datadog's per-host + per-feature + per-log-volume pricing routinely surprises teams. For teams that need budget predictability Sentry is the safer choice.
Reviewer Voices
"The only observability I check before opening Datadog."
"Release tracking caught regressions in 30 minutes that QA missed for weeks."
"One vendor for the everything board."
"Watchdog anomaly detection paid for itself."