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Datadog vs New Relic

Side-by-side uptime and reliability comparison based on real monitoring data.

Datadog US1
Operational
New Relic
Operational
FeatureDatadogNew Relic
Current StatusOperationalOperational
24-Hour Uptime100.00%—
7-Day Uptime100.00%—
30-Day Uptime100.00%—
90-Day Uptime100.00%—
Recent Incidents (total)129
Active Incidents00
Avg. Resolution Time1h 25m1h 33m
Tracked Components40106

Datadog vs New Relic: Uptime and Reliability Analysis

When evaluating monitoring services for your stack, uptime and reliability are critical factors. Both Datadog and New Relic are widely used in the monitoring space, but how do they compare on actual measured reliability?

Based on DevHelm's continuous monitoring of their official status pages, Datadog currently reports a 30-day uptime of 100.00% while New Relic reports —. Uptime data may not be available for all periods.

Incident Frequency

Over the recent monitoring window, Datadog has logged 12 incidents while New Relic has recorded 9 incidents. Fewer incidents generally indicates more stable infrastructure, though the severity and duration of each incident matter as much as the raw count.

Mean Time to Resolution

Datadog resolves incidents in an average of 1h 25m. New Relic averages 1h 33m per incident. Lower resolution times mean less disruption to your application and users.

Component Coverage

Datadog exposes 40 trackable components on their status page, compared to 106 for New Relic. More components means more granular visibility into which parts of the service are affected during an outage. This is especially useful for targeted alerting and incident response.

Which Should You Choose?

Both Datadog and New Relic are production-grade monitoring services used by thousands of companies. Your choice should factor in reliability alongside features, pricing, and ecosystem fit. DevHelm tracks both services continuously — add them to your workspace to receive real-time alerts when either experiences issues.

Methodology

DevHelm monitors the official status pages of both services and computes uptime from their self-reported component status data. Uptime percentages reflect the proportion of time all components reported operational status. Incident counts and resolution times come from vendor-published incident timelines. This comparison uses the same data source and methodology for both services to ensure a fair comparison. Data is refreshed every few minutes and aggregated daily.

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