If you’ve narrowed your observability search down to two names, it’s almost always these two. Datadog vs New Relic is the comparison every growing engineering team eventually runs into, because both platforms genuinely compete at the top of the market — and both will happily sell you more than you need if you’re not careful. The short version: they’re built around different philosophies, not just different price tags, and that difference matters more than any feature checklist.
Datadog grew up as an infrastructure and ops platform that later added deep application performance monitoring (APM). New Relic grew up as an APM tool for developers that later added infrastructure, logs, and everything else. Both have converged into full observability suites, but their DNA still shows in how each product feels day to day — and in who ends up happiest using it.
What is Datadog?
Datadog is a cloud monitoring and security platform that unifies infrastructure metrics, APM traces, log management, real user monitoring, synthetic testing, and security monitoring in a single pane of glass. Its biggest strength is breadth: over 800 integrations, dashboards that let you jump from an alert to a trace to the underlying logs and host metrics without switching tools, and a genuinely strong on-call/alerting workflow. Ops and SRE teams tend to gravitate toward Datadog because it was built for exactly that “one alert fired, now investigate everything” workflow.
The trade-off is pricing complexity. Datadog charges per host, per product — APM, infrastructure, logs, RUM, and synthetics are each their own SKU — which means costs can stack quickly as you turn on more features, and predicting your monthly bill takes real effort.
What is New Relic?
New Relic is an observability platform built around a single usage-based pricing model instead of a pile of per-product SKUs. Its historical strength is deep, code-level APM — the kind of stack traces and transaction tracing that developers actually live in when debugging a slow endpoint. New Relic has also leaned hard into OpenTelemetry, offering native OTel ingestion without extra surcharges, which appeals to teams standardizing on open instrumentation instead of vendor-specific agents.
New Relic’s pricing shifted meaningfully in recent years: instead of paying per host, you pay for data ingested (with a genuinely free 100 GB/month tier, not just a trial) plus billable users by seat type (Basic, Core, Full Platform), across Standard, Pro, and Enterprise editions. There’s also a newer Core Compute option, still in public preview, that bills by compute units consumed rather than seats. For teams with more developers than servers — think a lean team running a handful of large hosts — this model is often dramatically cheaper than paying per host.
Datadog vs New Relic: side-by-side comparison
Here’s how the two actually stack up across the categories that matter most day-to-day, before we put it all in a quick-reference table.
APM depth
This is the category where the two products’ origins still show the most. New Relic built its reputation on code-level transaction tracing — you can drill from a slow request straight down to the specific database call or external service dragging it out. Datadog’s APM has closed much of that gap and adds strong distributed tracing across microservices, but it’s presented as one layer of a much bigger platform rather than the main event. If your team spends most of its day debugging application code rather than servers, New Relic’s APM view will likely feel more native.
Infrastructure monitoring
Datadog is the stronger pick here, and it isn’t close. Host-level metrics, container and Kubernetes visibility, and network monitoring were Datadog’s original product, and it shows in the depth of dashboards and the sheer number of infrastructure-specific integrations. New Relic’s infrastructure monitoring is genuinely capable — and unlimited hosts under its usage-based plan is a real cost advantage — but it was added on top of an APM-first product, not built as the foundation.
Log management
Datadog’s log pipeline does real-time indexing with machine-learning-based pattern detection, and — critically — logs sit in the same interface as your traces and infra metrics, so you can pivot between them without losing context. New Relic handles log ingestion and correlation well enough for most teams, but its log-specific tooling hasn’t historically been treated as a flagship feature the way Datadog’s has.
Pricing model
This is the most consequential difference in 2026, and it’s shifted since either platform’s earlier days. Datadog still prices modularly: infrastructure, APM, logs, RUM, and synthetics are separate per-host or per-unit SKUs, so your bill grows with every host and every module you switch on. New Relic has moved to a usage-based model built on data ingested (with 100 GB/month free, not a time-limited trial) plus billable users by seat tier (Basic, Core, Full Platform) across Standard, Pro, and Enterprise editions — and it now also offers an optional Core Compute model, still in public preview, that bills by compute units consumed instead of seats. In practice, teams with lots of hosts and modest headcount often do better on Datadog’s per-host model, while teams with a handful of large hosts and lots of developers often do better on New Relic’s ingest-and-seat model. Model your own data volume and host count before assuming either is cheaper by default.
Dev vs ops usability
Think of it as: New Relic was designed for the developer debugging a regression, Datadog was designed for the on-call engineer investigating an incident. New Relic’s interface centers on code, deployments, and errors. Datadog’s centers on hosts, services, and the alert-to-trace-to-log investigation chain. Neither is “worse” — they’re optimized for different jobs, and plenty of teams end up needing both kinds of workflows, which is exactly why this decision is hard.
Integrations
Datadog’s integration catalog — over 800 at last count — is the widest in the category, covering everything from cloud providers to CI/CD tools to niche SaaS products. New Relic’s library is smaller but well maintained, and its standout advantage is native OpenTelemetry ingestion with no additional surcharge, which matters a lot if your team has already standardized on open instrumentation rather than vendor agents.
AI and anomaly detection
Datadog’s machine-learning-driven anomaly detection is mature and woven across metrics, logs, and traces, so unusual patterns surface automatically instead of requiring you to build every alert by hand. New Relic has been investing heavily in AI-assisted investigation and root-cause suggestions, but these features arrived later and still feel less deeply unified across the whole platform than Datadog’s equivalent tooling.
| Category | Datadog | New Relic |
|---|---|---|
| APM depth | Strong, broad-language tracing tied into infra context | Deeper code-level profiling; historically the stronger pure-APM tool |
| Infrastructure monitoring | Best-in-class; built for this from day one | Solid and unlimited hosts/containers under usage pricing, but less mature than Datadog’s |
| Log management | Real-time indexing, ML-based pattern and anomaly detection, tightly linked to traces | Capable log ingestion and correlation, but log-specific tooling is less differentiated |
| Pricing model | Modular per-host, per-product SKUs — flexible but stacks fast and is hard to forecast | Usage-based: data ingest (100 GB free/month) + billable users, or new Core Compute (preview) |
| Dev vs ops usability | Ops/SRE-first: alert-to-trace-to-log-to-host workflow is the star | Developer-first: code-level debugging and transaction tracing is the star |
| Integrations | 800+ integrations, arguably the widest ecosystem in the category | Strong integration library plus native, surcharge-free OpenTelemetry support |
| AI / anomaly detection | Mature ML-driven anomaly detection woven across metrics, logs, and traces | AI-assisted investigation features are improving but arrived later and feel less unified |
Verdict — which should you choose
Choose Datadog if you’re an infrastructure or SRE-led team running dozens of hosts, you want everything — metrics, logs, traces, security, synthetics — clickable from a single alert, and you have the budget and discipline to manage modular pricing. It’s the more complete ops platform, full stop.
Choose New Relic if your team is developer-heavy relative to your server count, you care most about deep code-level APM and fast root-cause debugging, or you want a usage-based bill that doesn’t punish you for adding hosts. The free 100 GB/month tier also makes it the easier platform to trial seriously before committing spend.
If you’re still unsure, the practical test is this: does your team think in terms of “which host is unhealthy” or “which function is slow”? Ops-first thinking points to Datadog. Developer-first thinking points to New Relic. Most teams outgrow the free tiers of both eventually — the question is just which paid model fits how your infrastructure actually grows.
A few situations worth calling out specifically. If you’re running a large fleet of containers or VMs with a small platform team keeping it all alive, Datadog’s infrastructure depth and 800-plus integrations will save you time that’s worth the modular pricing. If you’re a product engineering team shipping fast and debugging your own code more often than someone else’s servers, New Relic’s code-level APM and predictable ingest-based bill will likely feel like less friction day to day. And if data volume is your biggest cost driver — lots of logs, lots of custom metrics — run the numbers on New Relic’s free 100 GB tier and per-GB pricing before assuming Datadog’s per-host model is more expensive; for log-heavy, host-light setups, it frequently isn’t.
One more thing worth factoring in: switching costs. Both platforms lock in configuration, dashboards, and alerting logic that take real time to rebuild elsewhere. If you’re already deep into one platform’s ecosystem, the bar for switching should be “this is meaningfully better for how we work,” not just “this line item is a bit cheaper.”
FAQ
Is Datadog or New Relic cheaper?
It depends entirely on your infrastructure shape. Datadog’s per-host, per-product pricing tends to cost more as you add hosts and turn on more modules. New Relic’s usage-based model (data ingest plus billable users) tends to favor teams with fewer, larger hosts and more developers than servers. Neither is universally cheaper — model your actual usage before deciding.
Which one is better for APM specifically?
New Relic has historically had the edge in pure code-level APM depth and transaction tracing, which is why developer-heavy teams often prefer it. Datadog’s APM is strong too, and its advantage is context — traces are tightly linked to infrastructure metrics and logs in the same view.
Can I use both Datadog and New Relic together?
Technically yes, but it’s rare and usually not worth the overlapping cost. Most teams pick one as their primary observability platform and use the other only during a migration or trial period.
Does New Relic’s free tier actually work for production use?
Yes — the 100 GB/month free data ingest is a standing tier, not a time-limited trial, which makes it genuinely usable for small production workloads or side projects. Datadog’s free tier is much thinner and its full trial is time-limited to 14 days.
Which tool is easier to set up?
Both offer agent-based and OpenTelemetry-based instrumentation. New Relic’s OTel support has no ingest surcharge, which some teams find simpler if they’re already standardized on open instrumentation. Datadog’s own agent is mature and well-documented but adds vendor-specific setup steps per product you enable.
Is one of them better for small teams or startups?
Generally New Relic, mainly because of the free tier and the fact that unlimited hosts don’t add cost — a small team can monitor several services without worrying about host counts. Datadog can absolutely work for small teams too, but its per-host, per-product pricing means costs can climb faster as you add servers, so it’s worth watching your bill closely from month one if you go that route.
Datadog and New Relic are both strong enough that you can’t really go wrong on capability alone — the decision comes down to whether your team thinks like ops or like developers, and which pricing model matches how your infrastructure scales. For the bigger picture, see how both compare against the full top 10 list of server monitoring tools.