Asset 20 8 2
Does AI recommend your business? Run the free check →

Join 15,000 business owners, marketers and entrepreneurs. The Sunday newsletter you'll be annoyed only arrives once a week.

Article

Prometheus vs Grafana: What Each Does and Why You Use Both

Prometheus and Grafana aren't really competitors. Prometheus is an open source monitoring and alerting toolkit that collects and stores metrics as time series data. Grafana is an open source visualisation tool that turns data from Prometheus, and many other sources, into dashboards. Prometheus's own documentation says Grafana or other API consumers can be used to visualise the data it collects, which is why the two are so often run together.

The question usually comes from someone setting up monitoring for the first time and seeing both names in every tutorial. It's a fair question, because both can draw graphs and both can alert. But they sit at different layers of the stack, and once you see that, the choice becomes much simpler.

Prometheus vs Grafana at a glance

PrometheusGrafana
Main jobCollects, stores and queries metricsVisualises and explores data from many sources
Stores data itselfYes, time series stored locallyNo, it queries data sources
How it gets dataPulls (scrapes) metrics over HTTP from targetsConnects to data sources through plugins
Query languagePromQLUses each data source's query language, including PromQL
AlertingRules that generate alertsAlerting on the data it queries
OriginBuilt at SoundCloud, now a CNCF projectDeveloped by Grafana Labs
LicenceOpen sourceOpen source, AGPLv3 since 2021

What Prometheus does

Prometheus describes itself as a monitoring and alerting toolkit originally built at SoundCloud. It's now a standalone open source project maintained independently of any company, and it joined the Cloud Native Computing Foundation as the second hosted project after Kubernetes.

Its main features, from its own overview:

  • A multi dimensional data model, with time series identified by a metric name and key value labels
  • PromQL, a flexible query language for that data
  • No reliance on distributed storage, so single server nodes are autonomous
  • Metrics collected by pulling over HTTP, with a push gateway for short lived jobs
  • Targets found through service discovery or static configuration

The Prometheus server scrapes and stores the data, then runs rules over it to record new series or generate alerts. Most components are written in Go and ship as static binaries, so they're easy to deploy.

What Grafana does

Grafana Labs describes Grafana as an open source data visualisation and monitoring solution, with more than 150 plugins to bring your data sources into a single dashboard. Prometheus is just one of them. You can put metrics from Prometheus, logs from another system and business data from a database side by side on the same screen.

Grafana's own introduction to Prometheus explains the link nicely: Prometheus is a technology that collects and stores time series data, and Grafana uses PromQL queries against it to draw graphs such as disk input and output over time.

What Prometheus is good at watching

Prometheus explains metrics in plain terms: they're numerical measurements recorded over time. For a web server that might be request times, and for a database the number of active connections or queries. It gives a simple example of why they matter: if a web application slows down when requests are high, a request count metric lets you see the cause and add servers to handle the load.

It says it works well for recording any purely numeric time series, and that it fits both machine centric monitoring and highly dynamic service oriented setups. Its support for multi dimensional data collection and querying is a particular strength for microservices.

To get data in, you have three routes. Client libraries instrument your own application code. Special purpose exporters expose metrics from services such as HAProxy, StatsD and Graphite. And a push gateway handles short lived jobs that finish before Prometheus can scrape them. Grafana then sits on top and doesn't care which route the data took.

The limit worth knowing before you start

Prometheus is honest about one thing it isn't built for. Its overview says that if you need every figure to be completely accurate, such as for per request billing, Prometheus isn't a good choice, because the collected data likely won't be detailed and complete enough. It suggests using another system for billing data and Prometheus for the rest of your monitoring.

It's also designed to keep working when everything else is on fire. Each Prometheus server is standalone and doesn't depend on network storage or other remote services, so you can rely on it during an outage. That's a design choice worth copying for any monitoring setup.

Work with me

Want AI doing the heavy lifting in your marketing?

I build the systems that handle the boring 80 percent, so you get your week back. Done properly, with the human kept in.

How the two fit together

  1. Instrument your applications with Prometheus client libraries, or use exporters for services like HAProxy and StatsD.
  2. Run a Prometheus server to scrape those targets and store the metrics.
  3. Write alerting rules in Prometheus for the conditions that need a human.
  4. Add Prometheus as a data source in Grafana.
  5. Build Grafana dashboards with PromQL queries, and add other data sources as you need them.

A hosted rival is compared in the Datadog and Grafana comparison.

When you might use only one

You could use Prometheus alone with its built in graphing for quick checks, or with a different dashboard tool. You could use Grafana without Prometheus if your metrics live elsewhere, for example in a cloud provider's monitoring service or a database. And if you'd rather not run either yourself, hosted platforms bundle both jobs.

I've compared the best observability tools if you want the bigger picture, and there's a list of Grafana alternatives if you're weighing other dashboard tools.

My verdict

Don't choose between them. Choose Prometheus to collect and store your metrics, choose Grafana to see them, and run both. It's an open source pairing with no licence costs and plenty of documentation from both projects. Just keep billing and anything that must be exact out of Prometheus, as its own docs advise.

Licences and plans are covered in our Grafana free tier guide.

Frequently asked questions

Is Prometheus the same as Grafana?

No. Prometheus collects and stores metrics, and Grafana visualises data from Prometheus and many other sources.

Can Grafana work without Prometheus?

Yes. Grafana connects to many data sources through plugins, and Prometheus is only one of them.

Is Prometheus free?

Prometheus is an open source project maintained independently of any company and hosted by the Cloud Native Computing Foundation.

What is PromQL?

PromQL is Prometheus's query language. Grafana uses PromQL queries to graph Prometheus data.

When should you not use Prometheus?

Prometheus says it isn't a good choice when you need completely accurate data, such as per request billing.

Published and maintained by the Lilach Bullock team, covering marketing, AI and business growth.
Your buyers are asking AI who to use. Does it say you?

See for free whether ChatGPT, Claude, Perplexity, Gemini and Google name you, and get the plan to become the answer.

Check my AI visibility →
Sundays only

Get the Sunday newsletter.

One email a week. AI experiments, marketing tactics, and the workflows Lilach is building right now in her own business.

Subscribe free

Let’s get your marketing running on AI.

Book a free 30-minute call

We figure out what you need, where AI fits in, and what working together would look like.

Book the call →

Or take the 30-second calculator

You’ll see the hours and the money quietly leaking out of your week, and the three workflows worth building first.

Take the calculator →

Or grab the free AI resource library

Prompt packs, templates, checklists, and swipe files. The exact tools I build for paying clients. Yours, free.

Get the library →
Keep reading

More from the blog.