SigNoz vs Grafana

SigNoz and Grafana both show up when someone searches for a self-hosted observability tool, but they are not really competing for the same job. SigNoz is a single OpenTelemetry-native application that collects, stores, and displays metrics, logs, and traces itself. Grafana is a dashboard and alerting layer that queries a data source you run separately — Prometheus for metrics, Loki for logs, Tempo for traces, or any of dozens of others. Put plainly: one is a platform, the other is a lens you point at a platform you still have to build. That framing decides almost every other comparison on this page.

One integrated app vs. a stack you assemble

SigNoz ships as a multi-container application — a Go/TypeScript backend backed by ClickHouse for storage, with a bundled OpenTelemetry Collector in front that your services send OTLP data to directly. Point your instrumentation at SigNoz and you are done: metrics, logs, and traces land in one place, correlated, queryable from one UI. Its core is MIT-licensed, though it follows an open-core model — enterprise SSO and advanced RBAC sit behind a paid tier, while the observability core itself is fully open. It rates a realistic 4 GB of RAM and a 4 out of 5 install difficulty, because you are standing up ClickHouse alongside the app, not dropping in a single binary.

Grafana ships as one container, and that simplicity is deceptive. Out of the box, a fresh Grafana instance has no metrics, no logs, and nothing to alert on — it needs at least one data source configured before it does anything useful. In practice that means Prometheus for metrics, Loki for logs, Tempo for traces, or some mix of these, each its own service with its own storage, retention, and upkeep. Grafana itself is AGPL-3.0, rates a lighter 1 GB of RAM and 2 out of 5 difficulty — genuinely one of the easier containers to bring up — but that difficulty score is for Grafana alone, not for the observability stack most people actually want when they type "self-hosted Grafana" into a search bar.

Signals: collected vs. visualized

This is the real axis of the comparison, and it is worth being explicit about it rather than letting "Grafana" stand in for a whole ecosystem it doesn't include. SigNoz collects, stores, and queries metrics, logs, and traces itself, with OpenTelemetry as the native ingestion path — no separate time-series database, log store, or trace backend to run and size. Grafana collects nothing on its own. It is a query and visualization layer: connect it to Prometheus and it draws metrics, connect it to Loki and it draws logs, connect it to Tempo and it draws traces, and it can show all three side by side once those backends exist. That is Grafana's actual strength — a single pane of glass across systems you may already be running for other reasons — but it is not the same claim as "collects your telemetry."

Footprint, measured

Both apps were installed fresh on identical GCP e2-standard-2 instances running Ubuntu 26.04 and measured idle at first boot in August 2026. SigNoz came in at ~501 MB idle. Grafana alone measured ~154 MB idle and ~1.45 GB disk — but that number is for Grafana by itself, with no Prometheus, no Loki, and nothing feeding it data. Add a working metrics backend and the real footprint of a Grafana-centered stack climbs well past that figure; Prometheus alone typically wants a comparable or larger share of RAM than Grafana does. SigNoz's 4 GB documented floor (the ClickHouse comfort figure) already assumes the whole platform, collector included — there is no second bill coming later for a backend you forgot to budget for. If you are comparing "what does it cost to get a working observability setup running," SigNoz's number is closer to the true total; Grafana's is the cost of the easiest ten percent of the job.

Setup and ongoing upkeep

SigNoz installs via its Foundry installer, which brings up the application, the bundled collector, and ClickHouse together — one deploy step, several containers, and a database that benefits from someone paying attention as retention and volume grow. It is more to stand up front, but once it's running there is one thing to back up and one place to look.

Grafana installs in one line — docker run and you have a working dashboard server — but "working" means an empty shell until you point it at something. From there, upkeep is really the upkeep of whatever you connected: Prometheus's retention and storage, Loki's log volume, Tempo's trace sampling, each with its own version, its own disk growth, and its own failure modes, plus Grafana's own SQLite-by-default database for dashboards and alert rules, which is worth moving to Postgres once you depend on it.

License

SigNoz's core is MIT, one of the most permissive licenses available — the parts you would self-host for observability are unrestricted, with paid enterprise features clearly separated out. Grafana is AGPL-3.0, which carries network-copyleft obligations if you modify it and offer it as a hosted service to others. For straightforward internal self-hosting, neither license changes much day to day, but it is worth flagging plainly: Grafana's license is the stricter of the two if you ever plan to build a product on top of it.

Which should you self-host?

Pick SigNoz if you want one integrated OpenTelemetry-native application that gives you metrics, logs, and traces correlated in a single UI without assembling a stack of separate services — this is the closer answer to "self-hosted Datadog," and it is worth the heavier ClickHouse-backed box that comes with it.

Pick Grafana if you already have telemetry living somewhere — an existing Prometheus setup, a Loki install, metrics from another source entirely — and what you're actually missing is the dashboard and alerting layer to make sense of it. Grafana is also the right call if you specifically want a single pane of glass across multiple, unrelated backends rather than one unified app; that flexibility is its whole reason to exist, and it is genuinely excellent at it once the data sources behind it are in place.

If you are choosing purely by "what is the SigNoz vs. Grafana axis really about," it is this: SigNoz decides you should collect, store, and view telemetry in one app, and accepts the RAM cost of ClickHouse for that convenience. Grafana refuses to make that decision for you, stays light as a result, and leaves the collecting and storing as your homework.

Running either on a VPS

SigNoz's Foundry installer is built for a fresh VPS and expects the box it's running on to have the RAM to spare — a 4 GB-plus instance is the realistic starting point, not an 8 GB dream box, but not a $5 VPS either. Grafana will run comfortably on almost anything, including the same box as the services it monitors, but remember that its docker run one-liner is the beginning of the job, not the end: budget for whatever backend you pair it with before you size the VPS. Our SigNoz vs. OpenObserve and Prometheus vs. Grafana comparisons cover the two backends most people end up pairing with Grafana, and the Grafana deploy guide walks through the one-container install step by step.