Grafana vs Prometheus

Last reviewed Aug 26, 2026 · 583 words

Nobody should be choosing between these two, because they do different jobs: Prometheus scrapes and stores metrics, Grafana visualizes data it does not store. The search phrase "Grafana vs Prometheus" mostly means someone assembling their first monitoring stack and meeting both names at once — and the answer to that situation is that the standard stack is Grafana AND Prometheus, wired together in about five minutes. What is genuinely worth comparing is what each can do without the other.

Prometheus alone gets you further than you'd expect

Prometheus (Apache-2.0, 65,828 stars) is the complete monitoring engine: pull-based collection, a time-series database, PromQL for queries, and alerting rules built in. Its web UI on port 9090 includes an expression browser with basic graphs — ugly, but sufficient for debugging and for verifying that scrapes work. Critically, alerting does not require dashboards at all; plenty of production setups are Prometheus rules paging humans who rarely look at a graph. What you give up without Grafana is legibility: no saved dashboards, no variables, nothing you would put on a wall monitor.

Mind two defaults before exposing it to anything: metrics retention is 15 days unless you raise --storage.tsdb.retention.time, and there is no authentication whatsoever — keep it internal or put auth in front.

Grafana alone is only useful if you already have data

Grafana (AGPL-3.0, 76,422 stars) stores nothing but dashboards, users, and alert definitions. Its actual product is the data source plugin: Prometheus is the most common backend, but the same interface graphs logs from Loki, time series from InfluxDB, plus PostgreSQL, Elasticsearch, and dozens more through its plugin ecosystem. So Grafana without Prometheus is a perfectly reasonable deployment — if some other system is holding the numbers. Grafana without any data source renders nothing.

Deployment is one container (grafana/grafana-oss:latest, port 3000) with two catalogue gotchas that burn newcomers: the default login is admin/admin, so set GF_SECURITY_ADMIN_PASSWORD before first start, and the container runs as UID 472, so chown the data volume to match or it will fail to boot. Budget 512 MB of RAM for either tool; the pair fits comfortably in about 1 GB before exporters.

The five-minute wiring

The stack that most people actually want: run both containers, add http://prometheus:9090 as a data source in Grafana, then import a community dashboard by ID from grafana.com. With node-exporter on each host you get a full Linux fleet view in an evening. Both tools rate Medium difficulty in the catalogue, but honestly the hard 80% is Prometheus — scrape configs, retention, cardinality — while Grafana is mostly pointing and clicking. If even that sounds like more machinery than your single server needs, Netdata vs Prometheus covers the zero-config alternative.

Decision table

What I'd do

Deploy Prometheus first and confirm it is scraping something real, because every Grafana problem downstream is easier to debug when you trust the data layer. Add Grafana the same afternoon — the pairing is the whole point, and doing it in that order teaches you PromQL just well enough to build dashboards that mean something.