New Relic vs OpenObserve: A Complete Comparison for 2026

The clearest way to understand these two platforms is to ask where your telemetry physically lives, because the answer decides almost everything else. OpenObserve writes every log, metric, and trace as Apache Parquet files onto plain object storage, your own S3, MinIO, or GCS bucket, with only metadata in a small database, and that single decision is the whole product: object storage is so much cheaper than the indexed storage traditional platforms use that OpenObserve claims up to 140x lower storage cost than Elasticsearch, which is what lets you stop deleting data to save money. It is open source, written in Rust, deploys as a single binary, and queries everything with SQL and PromQL.

New Relic holds your telemetry in NRDB, its own hosted backend, and charges for it with two numbers: $0.40 per GB ingested and $349 per month for every engineer who needs full access. You do not run the storage, scale it, or patch it, and in exchange for that convenience you send everything to New Relic's cloud and query it with NRQL, a proprietary language that is genuinely capable but keeps your data and your saved work inside the platform. It is a mature, unified observability suite with years of depth behind it.

That contrast used to come with an asterisk: cheaper storage, but a narrower and less capable product. In 2026 the asterisk is smaller. OpenObserve now unifies logs, metrics, traces, real user monitoring, session replay, and LLM observability in one binary, ships an O2 SRE Agent for automated root cause analysis, supports MCP, holds SOC 2 Type II and ISO 27001, and raised a Series A on the back of an AI-native push. What it still is not is a decade-deep managed platform: there is no auto-instrumenting agent, no thread-level code profiling, no mature digital experience suite, and an AI story that is real but young next to New Relic's.

So this comparison runs along a clean axis: a mature, fully managed platform priced by ingest and seats, against an open, object-storage-native platform priced by the gigabyte with no seats and a free self-hosted floor. If you want breadth, polish, and someone else running the backend, New Relic delivers it. If you want cheap retention, data you control, and costs that scale with volume rather than headcount, OpenObserve does a job New Relic's model was never built to do affordably. The rest of this maps where each bet pays off, using current 2026 pricing and product status.

Quick comparison at a glance

Platform architecture and philosophy

The split here is unusually wide, because the two platforms disagree about who runs the backend, what it is made of, and how you pay to keep data in it.

New Relic: one hosted database, one query language, priced by who needs access

New Relic puts logs, metrics, traces, and events into NRDB and makes all of it queryable through NRQL. The investigation experience follows directly: an alert fires, and you click from the alert to the APM trace to the surrounding logs to the infrastructure state without switching interfaces or query languages, because everything shares one backend. OpenTelemetry is native with no surcharge, ingest runs $0.40/GB past the free tier, and the free tier itself (100GB per month and one full platform user, forever) is usable indefinitely for a small team. Beyond that, cost concentrates in seats at $349 per month per full platform user. You never run or scale the storage, which is the convenience you are paying for, and the data lives in New Relic's cloud, which is the tradeoff.

OpenObserve: Parquet on object storage, OTLP-native, open source

OpenObserve is built in Rust, ingests exclusively over OTLP and compatible collectors, and stores everything as Parquet on object storage, with PostgreSQL holding only metadata. That storage model is the architecture: object storage costs a fraction of the index-heavy storage traditional platforms rely on, which is the source of the up-to-140x storage-cost claim against Elasticsearch, and partitioning plus caching keep queries fast by cutting the search space dramatically. It deploys as a single binary in a couple of minutes or a Helm chart, scales from one node to petabytes (a Fortune 100 user reportedly ingests over 4PB per day), and queries everything with SQL and PromQL rather than a proprietary language. The free self-hosted edition is full-featured under AGPL-3.0, and Self-Hosted Enterprise is free up to 50GB per day with SSO, RBAC, federated search, and audit trails.

The tradeoff against New Relic is instrumentation and operation. OpenObserve sees only what OTel exporters send it: there is no auto-injecting agent that instruments a host the moment it lands, and the OSS route means you run and scale the object storage and infrastructure yourself. What you get in return is a unified, open platform where retention is cheap enough to change how much data you keep, and where the telemetry can stay entirely inside your own cloud.

APM and distributed tracing

Both trace requests across services. The gap is about instrumentation depth, not whether tracing exists.

New Relic: agent-based depth with eBPF and Infinite Tracing

New Relic offers language-specific APM agents with thread-level CPU profiling that shows exactly which function is consuming cycles in production, plus eBPF-based eAPM for zero-code Kubernetes instrumentation on services you would rather not touch. Infinite Tracing collects 100% of your traces and retains the most significant ones instead of sampling blindly, which matters for catching the rare slow request. APM 360 ties frontend sessions to backend traces in one interface, and because RUM and APM share NRDB, that correlation needs no configuration. The strength is depth plus coverage: New Relic can instrument almost anything and profile inside the process.

OpenObserve: OTel-native tracing queried with SQL

OpenObserve ingests traces over OTLP and stores them alongside logs and metrics in the same object-storage backend, so a trace, its logs, and the surrounding metrics live in one place and query with the same SQL. Because it captures without aggressive sampling, high-cardinality trace data stays affordable to retain, and moving over from another OTel backend is a collector config change rather than a re-instrumentation project. What it lacks is method-level, in-process profiling: OpenObserve shows you the spans your instrumentation emits, not the call stack inside each service, and there is no auto-instrumentation for services that were never wired up. For pinpointing a slow method inside your own code, New Relic goes deeper; for unified, cheap, SQL-queryable tracing across an OTel-instrumented stack, OpenObserve is a strong and much less expensive fit.

Log management

Both make all ingested logs searchable, which puts them ahead of the indexed-versus-archived model. The difference is what retention costs and where the data lives, and this is where OpenObserve's architecture pays off most directly.

New Relic: flat per-GB, all searchable, no query fees

New Relic charges $0.40/GB past the free tier, and every ingested log is searchable through NRQL with no per-query charge. Run fifty broad queries during an incident or five narrow ones and the bill is identical. There are no indexing decisions, no tier routing, and no archive to configure. Seven-year retention without rehydration covers compliance cases, and because logs share NRDB with traces and metrics, cross-signal correlation is automatic. It is a genuinely capable log product; the cost pressure comes from ingest volume and from the seats needed to let people query it.

OpenObserve: Parquet on object storage, SQL at petabyte scale

OpenObserve stores logs as Parquet on object storage and queries them with SQL and full-text search at petabyte scale. Because the storage layer is object storage rather than a hot index, retaining large volumes for long periods costs a fraction of index-heavy platforms, and OpenObserve's own comparisons cite an 8 to 10x lower total cost than Datadog for equivalent workloads, driven mostly by that storage model plus the absence of per-host and per-user fees. Cloud pricing is $0.50/GB ingested and $0.01/GB queried, or the whole thing runs free if you self-host. What New Relic has that OpenObserve does not is the deeper analytics maturity and seven-year managed retention without you operating anything; what OpenObserve has is dramatically cheaper long-term retention and a query language every engineer already knows.

Infrastructure monitoring

New Relic's coverage is broad and polished; OpenObserve's is real and cheap but scoped to what OpenTelemetry and cloud APIs report.

New Relic: broad cloud coverage, gated by the full platform seat

New Relic covers Linux, Windows, and macOS with agentless cloud integrations for AWS, Azure, and GCP, plus solid Kubernetes monitoring, all included in the ingest-plus-seats model with no per-host fee. The consistent caveat applies: viewing infrastructure data during an incident requires a full platform seat, so an engineer without one provisioned cannot pull up host metrics at 2am. The data is there; access is priced per person.

OpenObserve: high-cardinality metrics on object storage, no per-node fee

OpenObserve pulls metrics via OTLP, Prometheus, and cloud APIs, including CloudWatch directly with no intermediate collector, and stores high-cardinality container and host metrics without the per-node pricing that makes Kubernetes monitoring expensive elsewhere. A single Helm chart plus native OTel gives you cluster visibility quickly, and PromQL support means existing Prometheus queries carry over. What it does not have is New Relic's breadth of managed cloud integrations or the polish of agentless setup, and because there are no seats, every engineer views infrastructure data at no extra cost, the opposite of New Relic's seat-gated access.

Digital experience and LLM observability

Both cover the frontend and, increasingly, AI workloads, but from different maturity and at very different prices.

New Relic carries a mature, analyst-recognized digital experience suite: Browser RUM, Mobile RUM across iOS, Android, React Native, and Flutter, Session Replay, Synthetic Monitoring, and Product Analytics, all correlated to backend traces through the shared NRDB, and it is a two-time consecutive Gartner Magic Quadrant Leader for DEM. Its AI Observability, generally available since June 2026, extends monitoring to LLM pipelines and AI framework behavior.

OpenObserve includes RUM and session replay in the platform with no per-session premium, which is a real cost difference at high traffic, though the frontend suite is younger and thinner than New Relic's, with no true synthetics or mature mobile crash analysis. Where OpenObserve is notably forward is LLM observability: it traces Amazon Bedrock model calls and Bedrock Agents using OpenTelemetry's gen_ai semantic conventions, can trace Claude Agent SDK pipelines including tool calls and MCP interactions, and maps those signals to the same trace context as the surrounding infrastructure, so a token-cost spike can be traced to its cause. For teams building AI applications who want that visibility cheaply and in the same tool as everything else, it is a genuine draw.

AI capabilities

Both have shipped modern AI, and both connect to coding agents through MCP. New Relic's engine is more proven; OpenObserve's has closed ground fast.

New Relic: an "always on" SRE Agent, still mostly in preview

New Relic's SRE Agent, introduced in February 2026, is designed as an always-on teammate that begins diagnosing an incident before an engineer has acknowledged the page, querying traces, reviewing logs, checking recent deployments, and producing a root cause hypothesis. The Agentic Platform around it adds a no-code agent builder, orchestration, an evaluation engine, and MCP support. Applied Intelligence, which groups related alerts and generates summaries, is generally available, and AI Observability reached general availability in June 2026. The honest caveat is maturity: the SRE Agent, much of the Agentic Platform, and the MCP server remain in preview, so the flagship pieces are a bet rather than a settled purchase.

OpenObserve: the O2 SRE Agent and AI Assistant

OpenObserve's AI story is real and moving fast, backed by a 2026 Series A and an AI-native product push. The O2 SRE Agent is an always-on agent that performs semantic analysis across logs, metrics, and traces, correlates alerts into incidents, and produces a root cause diagnosis with a fix recommendation when an alert fires, referencing historical incidents for pattern matching and improving over time, with an Insights feature that surfaces incident dimensions in under a minute. The AI Assistant converts natural language to SQL and PromQL, generates dashboards and alerts from plain English, and summarizes anomalies, and OpenObserve supports MCP so external agents can query your data. The honest caveats: these features are newer, live on the Enterprise tier with credit-based metering (free during preview), and have thinner real-world validation than New Relic's longer-running Applied Intelligence. The direction is impressive; the maturity gap is real, and it runs in New Relic's favor.

Incident management and alerting

Neither platform owns the full incident lifecycle, and they stop at different points.

New Relic's Applied Intelligence groups related alerts and generates AI-driven summaries, SLO tracking watches error budgets, and on-call scheduling is available through New Relic On-Call or external integrations, giving it a native paging path. OpenObserve alerts natively and routes to PagerDuty, Slack, Opsgenie, and ServiceNow, and its Enterprise tier adds AI incident management that correlates signals into incidents automatically. What neither provides is the full paging layer with on-call rotations, escalation policies, and phone or SMS delivery as a default product, or customer-facing status pages. OpenObserve leans on external tools for the paging itself; New Relic's On-Call product covers more of it but still stops short of status pages.

Pricing comparison

The two models diverge on both axes that matter: what a unit of data costs to keep, and whether people cost money. New Relic prices ingest plus seats; OpenObserve prices per gigabyte with no seats and a free self-hosted floor.

New Relic charges $349 per month per full platform user on Pro, plus $0.40/GB ingest past the 100GB free tier. OpenObserve Cloud charges $0.50/GB ingested and $0.01/GB queried (the $0.30/GB rate reflects a 30% annual-commitment discount), with 15 months of metrics retention and 30 days for logs and traces included, $0.02/GB per additional 30-day period for non-metrics data, and no per-host or per-user fees. The self-hosted open-source edition is free, and Self-Hosted Enterprise is free up to 50GB per day.

Scenario: 15 engineers needing full access, 2TB/month telemetry

The gap widens with two things: headcount, because New Relic charges per seat and OpenObserve does not, and retention, because object storage makes keeping data cheap where NRDB is metered. Flip to a three-engineer team and New Relic drops toward $1,900 while OpenObserve barely moves, since its cost never tracked people. The self-hosted column looks cheapest and can be, but the honest line item is the one without a number: running and scaling the object storage and infrastructure yourself, which needs real expertise at volume. For teams with that capacity the savings are large; for teams without it, OpenObserve Cloud captures most of the advantage without the operations.

One genuine point each way: New Relic's forever-free tier (100GB and one full user) is the most generous evaluation path in managed observability, and OpenObserve's free self-hosted edition and 50GB-per-day free Enterprise tier are a more radical kind of free, bounded only by the hardware you are willing to run.

Security, compliance, and deployment

Neither platform is a security product, but both carry the certifications procurement asks about, and the deployment models differ sharply.

New Relic holds SOC 2 Type II, HIPAA on Data Plus, and FedRAMP Moderate with expansion to High underway, which matters for public-sector work, and its Security RX feature (in preview) correlates vulnerability findings with engineering context rather than providing runtime protection. It has no ISO 27001 or PCI DSS, and no self-hosted option: all telemetry lives in New Relic's cloud.

OpenObserve is SOC 2 Type II and ISO 27001 certified, and its most distinctive security-adjacent property is structural: the free self-hosted and BYOC options mean telemetry can stay entirely inside your own cloud, sidestepping a category of residency and sovereignty concerns. It has no FedRAMP authorization and no runtime application security product, and self-hosting the OSS edition needs genuine infrastructure expertise. For federal procurement specifically, New Relic covers ground OpenObserve does not; for teams whose priority is keeping telemetry in their own environment under a recognized baseline, OpenObserve's model delivers that at far lower cost.

What each platform genuinely lacks

New Relic gaps worth knowing:

1. Seat costs at $349 per month per full platform user compound quickly with team size.
2. No open-source or self-hosted option, and no object-storage-cheap long-term retention model.
3. All telemetry lives in New Relic's cloud, with no customer-owned storage path.
4. NRQL is proprietary, so every dashboard and saved investigation is tied to the platform.
5. The SRE Agent, most of the Agentic Platform, and the MCP server remain in preview.
6. No status pages and no unlimited native on-call delivery.
7. No ISO 27001 or PCI DSS certification.

OpenObserve gaps worth knowing:

1. No auto-instrumentation; every service needs an OTel SDK or exporter, with no agent equivalent.
2. No method-level code profiling; tracing is span-level only.
3. Digital experience is younger and thinner than New Relic's, with limited synthetics and mobile depth.
4. No runtime application security product, and no FedRAMP.
5. The O2 SRE Agent and AI Assistant are newer, enterprise-tier and credit-metered, with thinner validation than New Relic's.
6. Self-hosting the OSS edition needs real infrastructure expertise; the UI and docs are still maturing.
7. AGPL-3.0 licensing and some enterprise-gated features draw the usual open-core scrutiny.
8. No status pages and no native on-call with phone or SMS delivery.

Final thoughts

The decision is ultimately about which operating model fits your team better: paying more for a mature managed service, or taking on more responsibility for lower costs and greater control.

New Relic is the better fit when breadth, maturity, and convenience matter most. It offers stronger digital experience monitoring, thread-level profiling, broad cloud integrations, a more established AI operations layer, and FedRAMP coverage. However, that convenience comes with ingest plus $349-per-seat pricing, a proprietary query language, and no self-hosted option.

OpenObserve takes the opposite approach, prioritizing retention economics and data ownership. Its object-storage architecture, per-GB pricing, OpenTelemetry focus, and self-hosted deployment make it attractive for teams that want to retain more telemetry without per-seat or per-host fees. The trade-off is no auto-instrumentation, no method-level profiling, less mature frontend and AI capabilities, and the operational burden of managing storage on the OSS path.

In practice, New Relic reduces operational effort at a premium, while OpenObserve reduces cost by giving you more control and responsibility. Model both against your actual ingest, retention, and headcount, then decide whether New Relic’s added depth is valuable enough to justify the higher cost and reduced ownership.

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