Datadog vs New Relic: Which Observability Platform Should You Use in 2026?
A practical comparison of Datadog and New Relic covering pricing, features, and which one makes sense for small teams watching their monitoring bill.
Updated 2026-09 · 2026
Datadog
Unified monitoring for infrastructure, applications, logs, and security.
Strengths
- +Broadest set of pre-built integrations (600+) for cloud, containers, and SaaS tools
- +Everything under one roof: infra, APM, logs, RUM, security monitoring
- +Strong Kubernetes and cloud-native observability
Weaknesses
- -Pricing is modular and stacks fast — hosts, APM, logs, and custom metrics all billed separately
- -Log indexing costs can spike unexpectedly for chatty applications
- -Requires active cost governance to avoid surprise bills
Best for
Teams that want a single vendor for the entire observability stack and are willing to manage a modular, usage-based bill.
New Relic
Cloud monitoring and observability platform for application performance and infrastructure.
Strengths
- +Generous free tier: 100GB/month data ingest plus one full platform user, permanently free
- +Single consumption metric (data ingest) instead of dozens of separate SKUs
- +Deep APM and distributed tracing heritage
Weaknesses
- -Fewer out-of-the-box integrations than Datadog
- -NRQL query language has a learning curve for teams used to point-and-click dashboards
- -Adding full platform users ($99+/user/mo on Standard) gets expensive as teams grow
Best for
Small teams and startups that want a real free tier and simpler, ingest-based pricing without a per-host penalty.
Feature Comparison
| Feature | ||
|---|---|---|
| Free tier | Up to 5 hosts, limited retention | 100GB ingest/mo + 1 full user, no host cap |
| Infrastructure monitoring pricing | $15/host/mo (Pro, annual) | Included in ingest-based pricing |
| APM pricing | $31/host/mo (Pro) | Included in ingest-based pricing |
| Log management | Separate ingest + indexing fees | Included in same data ingest pool |
| Pre-built integrations | 600+ | 500+ (fewer niche SaaS integrations) |
| Kubernetes support | Excellent, purpose-built agents/dashboards | Good, via Pixie/K8s integration |
| Alerting & AIOps | Watchdog anomaly detection | New Relic AI + applied intelligence |
| Custom dashboards | Drag-and-drop widgets | NRQL-based, more flexible but code-like |
| Distributed tracing | Yes, included in APM tier | Yes, core strength of platform |
| Synthetic monitoring | Add-on, priced separately | Included in ingest pricing |
| Real User Monitoring (RUM) | Add-on, priced per session | Included in ingest pricing |
| Pricing model complexity | High — many separate SKUs | Lower — mostly one ingest metric plus user seats |
The Verdict
Datadog wins if you want the deepest integration library and are comfortable managing a complex, modular bill. New Relic is the better default for small teams because its free tier is genuinely usable and its ingest-based pricing is easier to predict as you scale. If your monitoring spend keeps creeping up on Datadog, New Relic is the most realistic switch — not a toy alternative, but a full-featured platform with a saner cost model.
How to switch from Datadog to New Relic
- 1Export your current Datadog setup: pull all dashboards via the Dashboards API (JSON export) and all monitors via the Monitors API, and if you manage Datadog with Terraform, save your current .tf state as a reference.
- 2Sign up for New Relic's free tier and install the New Relic agents (APM, Infrastructure) on your hosts using the guided install flow.
- 3Recreate your dashboards in New Relic by converting the widgets from your exported Datadog JSON into NRQL queries.
- 4Rebuild your Datadog monitors as New Relic alert policies and conditions, mapping thresholds and notification channels (Slack, PagerDuty, etc.) one-to-one.
- 5Reconnect your cloud and infrastructure integrations (AWS, GCP, Kubernetes) through New Relic's integrations hub, checking off each one against your original Datadog integration list.
- 6Run Datadog and New Relic in parallel for 2-4 weeks to validate data and alerting accuracy, then decommission Datadog agents/monitors and cancel the subscription.
Datadog vs New Relic: common questions
How do I export my data from Datadog before switching to New Relic?+
Datadog doesn't offer a full historical data export — you can pull dashboards and monitors as JSON via the Dashboards API and Monitors API, and export metrics/logs via the API for a limited lookback window. There's no built-in 'export everything' button, so plan to recreate dashboards and alert logic manually rather than migrating raw time-series history.
What do I lose moving from Datadog to New Relic?+
You lose Datadog's larger integration catalog (some niche SaaS and infra integrations don't have New Relic equivalents yet) and its more polished drag-and-drop dashboard builder. You'll also need to rebuild alerting logic since Datadog monitors and New Relic alert conditions aren't directly portable.
Is New Relic's free tier actually enough for a small team?+
For a small team monitoring a handful of services, 100GB/month of ingest plus one full platform user is often enough to run APM, infrastructure, and basic dashboards. Teams with high log volume or multiple engineers needing full-platform access will exceed the free tier quickly and need to budget for ingest overage or additional user seats.
Does New Relic support the same integrations I'm using with Datadog?+
New Relic covers the major cloud providers (AWS, GCP, Azure), Kubernetes, and common languages/frameworks, but its integration list is shorter than Datadog's. Check New Relic's integrations directory against your current Datadog integration list before committing, especially for niche tools.
Will switching from Datadog to New Relic actually save money over time?+
For teams currently paying separately for hosts, APM, logs, and RUM on Datadog, consolidating into New Relic's single ingest-based price often reduces cost, especially at small-to-mid scale. Savings shrink as you add more full-platform users, since New Relic charges per full user on top of ingest — model both pricing pages against your actual host count and data volume before switching.
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