# New Relic vs Dash0: A Complete Comparison for 2026
Picture the same production incident running through two different companies. At the New Relic shop, someone with a $349/month Pro seat pulls up NRDB, pivots from the alert to the APM trace to the surrounding logs without ever leaving NRQL, and the SRE Agent may already have a hypothesis waiting by the time they sit down. At the Dash0 shop, an engineer who probably knows PromQL from their Prometheus days queries logs, spans, and metrics that were never converted out of OpenTelemetry format in the first place, priced by the million signals rather than the gigabyte or the seat, with zero minimum spend if nothing gets sent that month.
Neither company had to build it this way. New Relic chose its architecture in 2020, when it blew up its old per-host pricing and rebuilt around two numbers: how much data you send, and how many engineers need full access. That choice bought it a genuinely unified investigation experience and one of the most generous free tiers in the industry, and it cost it a seat-based ceiling that compounds hard with team size. Dash0 chose differently from day one in 2023: OpenTelemetry native, dashboards on the open Perses standard, pricing per signal with zero lock-in, built by a team that had already lived through the enterprise-observability grind once at Instana before IBM acquired it. **That's not a coincidence. It's the whole thesis: build the anti-enterprise-observability-vendor, and let the founders' scar tissue do the product design.**
The scope gap is real and worth naming upfront. New Relic is a mature, full-stack platform: infrastructure, DEM with Gartner recognition, error tracking, and an expanding Agentic Platform. Dash0 is three years old, deliberately narrow, still building website monitoring and shipping its AI suite in beta. **This comparison isn't about crowning a winner. It's about which bet, unified maturity at seat-based cost or open-standard youth at per-signal cost, fits the team you actually have.**
## Quick comparison at a glance
| Feature | New Relic | Dash0 |
|---|---|---|
| **Founded** | 2008 | 2023 |
| **Primary purpose** | Unified full-stack observability SaaS | OpenTelemetry-native observability engine |
| **Free tier** | Yes (100GB/month + 1 full platform user, forever) | Pure consumption, zero minimum |
| **Pricing model** | Per-user seats + data ingest (GB) | Per million signals (logs, spans, metrics) |
| **Query language** | NRQL (unified) | PromQL |
| **Query fees** | None | None (included in per-signal price) |
| **Dashboard format** | Proprietary | Perses (CNCF open standard) |
| **Instrumentation** | APM agents, eBPF (eAPM), or OTel | OTel operator (Java, Node.js, .NET) + manual SDKs |
| **APM / tracing** | Yes (Infinite Tracing, thread profiling) | Yes (OTel-native, Trace Graph) |
| **Code-level profiling** | Yes (thread profiling) | No |
| **Log management** | Yes ($0.40/GB, no query fees) | Yes ($0.60/million records, 30-day retention) |
| **Infrastructure monitoring** | Yes (broad OS coverage) | Yes (Kubernetes-native, resource-centric) |
| **Kubernetes-as-code** | Limited | Yes (PersesDashboard, PrometheusRule, SyntheticCheck CRDs) |
| **Real user monitoring** | Yes (Gartner DEM Leader, 2x) | Available (newer, session replay early stage) |
| **Session replay** | Yes | Early stage |
| **Synthetic monitoring** | Yes | Yes (with span correlation, IaC via Terraform/CRDs) |
| **Error tracking** | Via APM error analytics | No (errors surface via traces/logs) |
| **Incident management** | Via New Relic On-Call or integrations | Not included (integrates with PagerDuty, Opsgenie, ilert) |
| **AI capabilities** | Applied Intelligence (GA) + SRE Agent (Preview) | Agent0 (beta, specialized agent federation) |
| **MCP server** | Yes (Preview) | No (Agent Skills instead) |
| **Self-hosted / air-gapped** | No | No (SaaS-only) |
| **SOC 2 Type II** | Yes | Yes |
| **HIPAA** | Yes (Data Plus) | No |
| **FedRAMP** | Yes (Moderate, expanding to High) | No |
---
## Platform architecture and philosophy
The two founding stories point in almost opposite directions, and everything downstream in this comparison traces back to them.
### New Relic: one database, priced by data and by who gets to see it
New Relic puts logs, metrics, traces, and events into NRDB and makes all of it queryable through NRQL, so an alert-to-trace-to-log-to-infrastructure pivot never requires switching interfaces or learning a second query syntax. That's the payoff of eighteen years of building one thing well. The cost structure is two dimensions: $0.40/GB past the free 100GB/month, and $349/month per full platform user on Pro. The data side is genuinely easy to forecast. The seat side is where the bill actually lives for most teams, and it scales with headcount regardless of how much telemetry you send.
### Dash0: OpenTelemetry natively, Perses dashboards, priced per signal with zero lock-in as a stated design goal
Dash0 was built to ingest, store, and query OpenTelemetry data without ever converting it into a proprietary shape, which the founders, having watched what happens when legacy vendors bolt OTel support onto pre-existing systems, treat as close to a founding principle. Dashboards are built on Perses, a CNCF-backed open standard, so what you build in Dash0 exports and imports elsewhere without modification, a genuinely unusual commitment for a vendor whose business model depends on you not leaving. The Kubernetes Operator auto-instruments Java, Node.js, and .NET; other runtimes need manual OTel SDK setup, real ongoing engineering work that OneAgent-style auto-injection (which neither platform in this specific comparison offers, notably) would otherwise avoid.
Pricing is per million signals, logs, spans, metric data points, with zero minimum spend. Unlimited seats, no per-user fee at all, which inverts New Relic's entire cost model: a 30-person team on Dash0 pays the same platform cost as a 3-person team sending the same telemetry volume.
| Architectural factor | New Relic | Dash0 |
|---|---|---|
| Founding thesis | Unified database, seat-gated access | Open standards, per-signal, zero lock-in |
| Data storage | NRDB (proprietary, unified) | Unified OTel-native store |
| Query language | NRQL | PromQL |
| Dashboard format | Proprietary | Perses (CNCF open standard) |
| Per-seat fee | Yes ($349/mo full platform) | None (unlimited seats) |
| Instrumentation | APM agents, eBPF, or OTel (all native, no surcharge) | OTel operator (3 runtimes) + manual SDKs |
| Query fees | None | None |
| Company maturity | 18 years, public, enterprise-scale | 3 years, unicorn, 600+ customers |
[summary]
### Neither platform pages the human who needs to know
New Relic's investigation is unified and Dash0's data is open, but neither one gets anyone on the phone during an incident. Better Stack connects observability directly to on-call and incident response in one platform.
**From heartbeat monitoring to incident timelines to status pages, one platform for the whole reliability lifecycle.** [Start free.](https://betterstack.com)
[/summary]
---
## APM and distributed tracing
Both platforms are genuinely OTel-friendly, which is worth flagging since it isn't universal in this series, but they instrument differently and it shows up in what each one can see.
### New Relic: agent or eBPF or OTel, whichever fits the workload
New Relic offers language-specific APM agents with thread-level CPU profiling, eBPF-based eAPM for zero-code Kubernetes instrumentation, or plain OpenTelemetry with no surcharge, three paths, pick per workload. Infinite Tracing observes 100% of collected traces and retains the significant ones rather than sampling blindly, which catches the rare slow request that head-based sampling would drop. Thread-level profiling, seeing exactly which function is consuming cycles in production, is a real depth advantage Dash0's OTel-only tracing doesn't currently match.
### Dash0: Trace Graph, synthetic metrics from spans, and data that's never locked in
Dash0's Trace Graph turns a trace into a functional architecture diagram rather than a flat waterfall, genuinely useful once a trace has thousands of spans and the waterfall view stops being legible. Synthetic metrics, error rates and latency percentiles derived on demand from raw spans, don't bill separately since you already paid for the underlying spans. The Kubernetes Operator auto-instruments Java, Node.js, and .NET; everything else is manual OTel SDK setup, real ongoing work, though the payoff is that nothing you capture is locked into a proprietary format the way traces in NRDB, however smoothly they correlate today, ultimately are.
| APM / tracing | New Relic | Dash0 |
|---|---|---|
| Instrumentation | APM agents, eBPF, or OTel | OTel operator (3 runtimes) + manual SDKs |
| Code-level profiling | Yes (thread profiling) | No |
| Trace retention approach | Infinite Tracing (smart retention) | Standard retention (30 days) |
| Trace visualization | Waterfall + service map | Waterfall + flame graph + Trace Graph |
| Synthetic metrics from spans | Via NRQL | Included, no extra charge |
| Data portability | Moderate (NRQL/NRDB) | Full (OTel format, Perses dashboards) |
| APM pricing | Included in ingest + user license | $0.60 per million spans |
[summary]
### Tracing without seat math or per-service SDK rollout
New Relic charges per engineer who needs to see the trace, and Dash0 asks your team to instrument every service by hand. Better Stack's eBPF-based tracing captures HTTP, gRPC, and database traffic at the kernel level with zero code changes, priced purely by data volume.
**Full-fidelity distributed tracing from every service, priced by volume with no surprises.** [Explore Better Stack tracing.](https://betterstack.com/tracing)
[/summary]
---
## Log management
Neither platform indexes selectively, both make everything searchable, but they charge for very different units, and that difference matters more than it looks on paper.
### New Relic: flat per-GB, no query fees, seven-year retention available
New Relic charges $0.40/GB past the free 100GB/month, every log is searchable through NRQL with no per-query charges, and seven-year retention without rehydration is available for compliance needs. Investigate an incident with fifty broad queries or five narrow ones; the bill is identical either way.
### Dash0: per-signal, so a verbose log costs the same as a terse one
Dash0 charges $0.60 per million log records regardless of size, so a verbose error log with a full stack trace costs the same as a one-line health check, an inversion of byte-based pricing that rewards rich, detailed logging rather than penalizing it. Spam Filters drop noisy telemetry, redundant success logs, chatty health checks, before it counts against the bill, a genuinely useful lever New Relic's flat-rate model doesn't offer or need. The catch is the reverse case: high-volume, low-content signals (thousands of tiny metric-like log lines, say) get expensive fast under per-signal pricing in a way per-GB pricing wouldn't punish. Retention defaults to 30 days against New Relic's seven-year ceiling, and PromQL is the only query language, a real gap for teams whose engineers mostly know SQL.
| Log management | New Relic | Dash0 |
|---|---|---|
| Pricing model | $0.40/GB (100GB/month free) | $0.60/million records |
| Query fees | None | None |
| Verbose vs. terse logs | Larger logs cost more | Same cost regardless of size |
| Pre-billing filtering | Not really available | Yes (Spam Filters, one-click) |
| Query language | NRQL | PromQL only |
| Max retention | 7 years, no rehydration | 30 days default |
[summary]
### Log search with no per-seat gate and no per-signal math
Both platforms avoid the indexed-versus-archived trap, but one still charges per engineer to view the data and the other counts every log line as a billable unit. Better Stack stores everything in one SQL-queryable warehouse at $0.10/GB with no query fees.
**Unified log management with SQL search, live tail, and no indexing surprises.** [See how it works.](https://betterstack.com/logs)
[/summary]
---
## Infrastructure and Kubernetes monitoring
New Relic covers more ground across more operating systems. Dash0 goes deeper into Kubernetes specifically, and does it with a genuinely modern operating model.
### New Relic: broad OS coverage, gated by seat
New Relic covers Linux, Windows, and macOS with no-agent cloud integrations for AWS, Azure, and GCP, and solid Kubernetes monitoring, all included in the ingest-plus-seats model with no per-host fee and no cardinality penalty. The now-familiar caveat applies: viewing infrastructure data during an incident requires a full platform seat, so an engineer without one provisioned can't see host metrics at 2am.
### Dash0: Kubernetes-as-code, resource-centric, and honestly narrow beyond that
Dash0's Kubernetes Operator goes further than most platforms for the estates it targets: it auto-instruments supported workloads, collects pod logs and cluster metrics, and synchronizes PrometheusRule and PersesDashboard CRDs directly from your cluster, so alerts, dashboards, and synthetic checks can all be defined as Kubernetes resources, version-controlled in Git, deployed through CI/CD. That's a materially more modern operating model than New Relic's console-and-NRQL approach for teams that already think in GitOps terms. Resource-centric views scope metrics, logs, and traces to the pod or service that produced them, aligning cleanly with OpenTelemetry's resource model. The honest limit: this is Kubernetes-native depth with comparatively little support outside it, no Windows agent story, no macOS, nothing resembling New Relic's broad OS coverage.
| Infrastructure monitoring | New Relic | Dash0 |
|---|---|---|
| OS coverage | Linux, Windows, macOS | Kubernetes-first |
| Kubernetes depth | Yes, console-first | Yes, CRD-native (dashboards, alerts, synthetic checks) |
| Pricing | Included in ingest + user license | $0.20 per million data points |
| Cardinality penalty | No | No |
| Metric retention | 30 days raw, 13 months aggregated | 13 months |
| Access to view data | Full platform user required | Included for all seats (no per-user fee) |
---
## AI capabilities
Both companies are mid-buildout here, and both are honest that the flagship feature is early. New Relic's is in Preview; Dash0's is in beta. Neither is production-hardened yet.
### New Relic: SRE Agent, promising architecture, still Preview
New Relic's SRE Agent, launched February 2026, fires automatically when an alert triggers and investigates without prompting: querying traces, reviewing logs, checking recent deployments, producing a root cause hypothesis. Applied Intelligence, alert grouping and summarization, is GA and has been for years, a real and mature capability sitting alongside the newer, unproven agent. The Agentic Platform adds a no-code agent builder and MCP support, also Preview.
### Dash0: Agent0's federation of named specialists, all beta
Agent0 is architecturally more ambitious than a single assistant: six named, specialized agents, the Seeker investigates alerts, the Oracle generates PromQL from natural language, the Pathfinder guides instrumentation of new services, the Threadweaver analyzes complex traces, the Architect generates dashboards and alert rules, and the Lookout surfaces problematic web sessions. Each agent exposes its own reasoning, making conclusions inspectable rather than opaque, and the roadmap extends to autonomous migration, cost optimization, and security detection agents. It's precisely the kind of ambitious, multi-agent bet a $110M Series B raised specifically to fund it would produce.
The honest comparison: New Relic has no MCP server that's GA either (it's Preview, same maturity tier as Dash0's Agent Skills-based approach), so neither vendor has a shipped, production-grade AI-assisted developer workflow today. Applied Intelligence is New Relic's one genuinely mature AI capability; Agent0's reasoning transparency is Dash0's most distinctive one.
| AI capability | New Relic | Dash0 |
|---|---|---|
| Alert grouping/summarization | Yes (Applied Intelligence, GA) | Basic |
| Autonomous incident investigation | SRE Agent (Preview) | Agent0's Seeker (beta) |
| MCP server | Preview | None (Agent Skills + CLI instead) |
| Reasoning transparency | Not chain-shown | Yes, each agent exposes its reasoning |
| Instrumentation guidance agent | No | Yes (the Pathfinder) |
| Dashboard/query generation via AI | Via Agentic Platform (Preview) | Yes (the Architect, the Oracle) |
[summary]
### AI investigation that's still finding its footing on both sides
Applied Intelligence is mature but the SRE Agent is Preview; Agent0 is ambitious but every piece is beta. Better Stack's AI SRE activates autonomously during incidents and delivers its hypothesis into a live incident with the responder already paged, GA today.
**Autonomous root cause investigation connected to on-call, incidents, and status pages.** [See the AI SRE.](https://betterstack.com)
[/summary]
---
## Digital experience and error tracking
This is the section where New Relic's eighteen years show most clearly, and Dash0's youth shows just as clearly on the other side.
New Relic's DEM suite is complete: browser and mobile RUM (iOS, Android, React Native, Flutter), session replay, synthetic monitoring, product analytics, and two consecutive years as a Gartner Magic Quadrant Leader for DEM. Error tracking runs through APM's error analytics, connected to traces and thread profiling, though without dedicated issue-grouping the way a purpose-built error tracker offers.
Dash0's website monitoring, built on the Dash0 Web SDK and OpenTelemetry standards, captures Core Web Vitals, sessions, and page views across three views (Overview, Web Vitals, Sessions), with IP anonymization by default. By Dash0's own admission, session replay is early stage, product analytics and funnel analysis are limited, and there's no dedicated error tracking product at all, errors surface via span status codes and log records rather than through issue grouping.
| Digital experience | New Relic | Dash0 |
|---|---|---|
| Browser + mobile RUM | Yes (Gartner DEM Leader, 2x) | Web-only (mobile not covered) |
| Session replay | Yes | Early stage |
| Synthetic monitoring | Yes | Yes (with span correlation) |
| Dedicated error tracking | Via APM error analytics | No (via traces/logs) |
| Core Web Vitals | Yes | Yes (LCP, CLS, INP, p75 analysis) |
---
## What each platform doesn't do
New Relic's gaps are the ones you'd expect from a mature seat-priced SaaS platform: no self-hosted option ever, and a genuine access-restriction pattern where infrastructure, DEM, and APM data all sit behind a $349/month seat regardless of who needs to see it during an incident.
Dash0's gap list is longer, a fair reflection of three years versus eighteen. No dedicated error tracking product. No HIPAA or FedRAMP. No self-hosted option either, so both platforms share that SaaS-only limitation. No MCP server yet, notable since several competitors in this series already have one GA. Mobile RUM isn't covered at all. And, same as New Relic, no incident management or on-call scheduling of its own.
| Gap | New Relic | Dash0 |
|---|---|---|
| Incident management / on-call | No (external tools) | No (external tools) |
| Self-hosted option | No | No |
| Dedicated error tracking | Limited (via APM) | No |
| Mobile RUM | Yes | No |
| MCP server | Preview | None |
| HIPAA / FedRAMP | Yes / Yes | No / No |
| Free tier | 100GB + 1 user, forever | Zero minimum, pure consumption |
| Status pages | No | No |
---
## Pricing comparison
**Scenario: 15 engineers, Kubernetes-heavy stack, moderate telemetry volume**
| Cost component | New Relic (Pro, annual) | Dash0 (per-signal) |
|---|---|---|
| User licenses | $5,235/month (15 x $349) | $0 (unlimited seats) |
| Logs (moderate volume) | ~$160/month (minus free tier) | ~$300-500/month ($0.60/M records) |
| Traces | Included in ingest | ~$200-400/month ($0.60/M spans) |
| Metrics | Included in ingest | ~$100-200/month ($0.20/M data points) |
| **Estimated monthly total** | **~$5,395-5,595/month** | **~$600-1,100/month** |
At this profile the gap is dramatic and runs entirely through the seat line: 15 engineers is where New Relic's per-user model starts to bite hard, while Dash0 charges nothing extra for headcount at all. Flip the variables, a 2-person platform team sending enormous telemetry volume, and the picture changes: New Relic's cost stays anchored to two seats plus data, while Dash0's per-signal pricing could climb faster than expected if that volume is heavy on small, frequent signals rather than large batched ones.
The asterisk that matters most: Dash0's total here doesn't include incident management (still needs PagerDuty or similar, roughly $245-415/month for five responders, same gap New Relic has too), and doesn't include anything New Relic's DEM suite or error tracking would need to replace. Compare total capability, not the sticker price alone.
| Pricing factor | New Relic | Dash0 |
|---|---|---|
| Free tier | 100GB + 1 user, forever | Zero minimum, pure consumption |
| Cost anchored to | Engineer headcount + ingest | Signal count (logs, spans, metrics) |
| Per-seat fee | $349/month (full platform, Pro) | None |
| Query fees | None | None |
| Self-serve start | Yes | Yes |
| Enterprise negotiation norm | Standard | Not yet established (young company) |
[summary]
### Volume pricing without the seat tax or the incident-response gap
Dash0 proves headcount doesn't have to drive your observability bill, but neither platform pages your on-call engineer. Better Stack combines volume-priced logs, metrics, and traces with on-call scheduling, incident management, and status pages, one platform, one bill.
**Fewer vendors, fewer context switches, and a single place for the full reliability workflow.** [Talk to us.](https://betterstack.com)
[/summary]
---
## Final thoughts
Run one quick calculation before reading anything else in this section: your engineer count times $349, against your monthly telemetry volume in millions of signals times roughly $0.40-0.60. For most teams that single comparison decides more of this than any feature table does, because **New Relic's cost is a function of headcount and Dash0's is a function of data, and those two things rarely grow at the same rate inside a single organization.**
If your team is large relative to your telemetry volume, a big engineering org running lean infrastructure, Dash0's zero-seat-fee model is the more honest reflection of your actual usage, and its OpenTelemetry-native architecture means you're never locked into a proprietary format the way NRDB and NRQL, however smooth day to day, ultimately are. **The tradeoff is real: you're betting on a three-year-old company's beta AI suite, its narrower DEM coverage, and its Kubernetes-first scope over New Relic's eighteen years of mature, Gartner-recognized breadth.**
If your team is small relative to your data volume, or if mobile RUM, dedicated error tracking, and a more mature (if still-Preview) AI roadmap matter to your evaluation, New Relic's unified platform and generous free tier make it the lower-friction choice, and the seat cost that hurts larger teams barely registers for a five-person team generating heavy telemetry. **Neither answer is universally right, which is exactly why running your own numbers, not the vendor's marketing math, is the only way this actually gets decided.**
[summary]
### The layer neither platform has built
Neither New Relic nor Dash0 includes uptime monitoring, on-call scheduling with phone and SMS, incident management, or customer-facing status pages as part of the core platform. Better Stack brings all of that together with logs, metrics, and traces, with usage-based pricing and no per-seat or per-signal surcharges.
**The full reliability lifecycle in one place. Start free, no credit card required.** [Try Better Stack.](https://betterstack.com)
[/summary]