D
Datadog
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New Relic

Datadog vs New Relic

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

🏆 Quick Verdict

Datadog leads on depth of observability and integrations. New Relic leads on pricing transparency and a more generous free tier. Both are enterprise-grade APM platforms; the choice often comes down to team size and budget.

Overall Scores

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

New Relic

overall 4.3/5
ease Of Use 3.8/5
design 4/5
features 4.8/5
value 4/5
support 4.3/5

Feature Comparison

Datadog Advantages

  • Similar feature set

Both Have

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

New Relic Advantages

  • releaseTracking

Pricing Comparison

Datadog

Free starting

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

New Relic

Free starting

  • free: Available
  • standard: $49/mo
  • pro: custom
  • enterprise: custom

Pros & Cons

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
New Relic

Pros

  • + Generous free tier (100GB/month)
  • + Full-stack observability platform
  • + Strong APM capabilities
  • + Excellent NRQL query language
  • + Unified billing for all features

Cons

  • Expensive beyond free tier
  • UI can feel cluttered
  • Agent performance overhead
  • Steep learning curve

In-Depth Analysis

Datadog's integration library (600+) is unmatched. Whether you're monitoring AWS Lambda, Kubernetes pods, Nginx, Redis, or a custom application, Datadog likely has a native integration with zero-config setup. The unified dashboard experience — metrics, logs, traces, and RUM all in the same tool with cross-linking — is genuinely excellent for complex distributed systems.

New Relic's pricing model changed dramatically in 2020: they moved to a data-ingest + user-count model instead of per-host pricing. This created a genuinely generous free tier (100GB of data/month, 1 full platform user, unlimited basic users) that lets small teams use New Relic's full platform without paying. Datadog's free tier is more limited and its per-host + per-product pricing model is harder to predict.

The agent performance overhead comparison often surprises teams evaluating these platforms. Datadog's agent is generally lighter than New Relic's older APM agents. New Relic's newer agents have improved, but some teams with CPU-sensitive applications still report more overhead from New Relic instrumentation.

NRQL (New Relic Query Language) is often cited as a reason teams choose New Relic. It's a SQL-like query language for all New Relic data that makes custom queries, dashboards, and alerts more intuitive than Datadog's metrics syntax. For teams that build a lot of custom dashboards, NRQL's familiarity reduces the learning curve.

Who Should Choose What?

Choose Datadog if:

Large engineering teams who need the deepest integration library and unified observability across complex infra

Choose New Relic if:

Teams wanting predictable pricing with a generous free tier and a SQL-like query language

Ready to Get Started?

Try both platforms free and see which one feels right.