# Prometheus vs Grafana: The Key Differences to Know
Prometheus and Grafana are open-source solutions for processing and monitoring
time-series data. Although some of their features overlap, they differ
significantly in their strength. This article presents a quick overview of these
tools, their strengths and weaknesses, and how they compare.
Prometheus is an infrastructure monitoring tool created by SoundCloud but is now
an open-source project hosted on GitHub, with an active community behind it. It
[excels at data acquisition](https://betterstack.com/community/guides/monitoring/monitor-linux-prometheus-node-exporter/) through its
custom query language, which allows you to select and aggregate time-series data. The collected [metrics](https://betterstack.com/community/guides/monitoring/prometheus-metrics-explained/) can be viewed inside Prometheus's expression browser or
transferred to external systems via its HTTP API.
Grafana is an open-source data analytics and visualization web application
created by Grafana Labs. It lets you visualize time series data by compiling
them into charts, graphs, or maps and it even provides alerting when connected
to supported data sources.
In this article, we are going to perform a side-by-side comparison of Prometheus
based on the following criteria:
1. Functionality overview
2. Data acquisition
3. Data visualization
4. Deployment and installation process
5. UI and UX design
6. Easy integration
7. Documentation
8. Team management
9. Incident management and alerting
10. Pricing
## 1. Functionality overview
| Feature | Prometheus | Grafana |
| :----------------- | :--------------- | :--------------- |
| Data acquisition | ✔✔ | ✖ |
| Data visualization | ✔ | ✔✔ |
| Data storage | ✔ | ✔ |
| UI & UX | ✔ | ✔✔ |
| Team management | ✖ | ✔✔ |
| Easy deployment | ✔ | ✔ |
| Easy integration | ✖ | ✔ |
| Free plan | ✔✔ | ✔✔ |
✔ - partial or limited feature
✔✔ - complete feature
✖ - does not support
## 2. Data acquisition: Prometheus wins
Data acquisition is where Prometheus shines. It collects time-series data by
pulling it through its HTTP protocol. The collected data is subsequently stored
in a multi-dimensional data model, which can be identified by its metric name.
Prometheus also allows the user to use PromQL, its unique and powerful query
language, to query and aggregate time-series data from the previously mentioned
data model in real-time. The queried data can then be displayed as a graph or
table or sent to an external system.
PromQL follows the same syntax rules as Go, so if you are familiar with the
language, you should be able to learn PromQL rather quickly. A metrics explorer
is also available in Prometheus in case you need help finding the PromQL
expressions you need.
On the other hand, Grafana requires the user to set up an external data source,
such as Prometheus, before it can visualize such data. You can read more about
[how to visualize Prometheus metrics with
Grafana](https://betterstack.com/community/guides/monitoring/visualize-prometheus-metrics-grafana/) in the linked article.
Besides Prometheus, Grafana is compatible with more than a dozen different data
sources, such as Elasticsearch, Graphite, and InfluxDB. A complete list of all
compatible data sources can be found in Grafana's
[official documentation](https://grafana.com/docs/grafana/latest/introduction/).
Prometheus wins this round because Grafana cannot collect data on its own.
## 3. Data visualization: Grafana wins
Grafana excels at data visualization. It can compile time-series data from
external data sources into dashboards with charts, graphs, and maps. You can
then share the dashboards among team members or configure the dashboard to be
accessible publicly.
Grafana also allows you to customize existing dashboards by adding time filters,
changing the view mode, altering the graph legend, etc. For example, after
you've created your dashboards, you can use the time picker dropdown on the top
right corner to zoom in or out.
Managing different dashboards is also essential when you have multiple
dashboards for your project. Grafana also provides you the option to put
dashboards into separate folders.
Prometheus can also generate charts and graphs from collected data using its
expression browser. However, it is missing a lot of features when compared to
Grafana. For example:
- It does not come with dashboard functionalities, meaning you cannot combine
multiple charts.
- There is no drag-and-drop functionality.
- You have to input queries to see results, which means you can only see one
chat at a time.
- It doesn't support sharing or team management.
- You cannot integrate events and alerts into its graphs.
- A time filter is also provided in Prometheus, but it lacks features compared
to Grafana.
Grafana is the clear winner for this round. In fact, Prometheus' official
documentation
[recommends Grafana as its visualization solution](https://prometheus.io/docs/visualization/grafana/).
## 4. Easy installation and deployment: Grafana wins
Prometheus is easy enough to setup as all you need to do is
[download the appropriate binary](https://prometheus.io/download) for your
operating system and execute it.
[Official Docker images](https://prometheus.io/docs/prometheus/latest/installation/#using-docker)
are also available for all Prometheus services.
Self-hosting Grafana is also quite easy as a multitude of
[options](https://grafana.com/docs/grafana/latest/setup-grafana/installation/)
are available depending on your operating system. A fully managed cloud service
is also available to get you up and running in minutes. Since the Prometheus
project provides no corresponding service, Grafana takes this round.
## 5. UI and UX design: Grafana wins
Regarding User Interface and User Experience design, Grafana is the clear
winner. It has a beautifully designed interface that is super easy to navigate.
All the navigational links are placed on the left, and on the right, you can
create dashboards, alerts and configure settings. The latest version of Grafana
also comes with a light/dark mode that follows your system setting.
Prometheus' UI design could be more impressive in comparison. Even though it
allows you to create charts and graphs, there is little you can do to customize
things.
## 6. Ease of integration: Grafana wins
When it comes to integration with your project, Prometheus and Grafana have
different procedures. Prometheus requires the use of
[client libraries](https://prometheus.io/docs/instrumenting/clientlibs/) to send
data to the Prometheus server. The server can then query, select and filter
required data using PromQL. This process does require a lot of coding.
Grafana assumes you have already collected enough data in a compatible format so
all you need to do is connect your data source through its user interface.
## 7. Documentation: tie
Both Prometheus and Grafana offer excellent documentation. Prometheus has well-
laid-out documentation, which includes basic concepts, PromQL, visualization
techniques, client libraries, security settings, alerting rules, best practices,
and tutorials. The tutorials demonstrate how to use Prometheus in a real-life
application.
Grafana also has well-written documentation but primarily focuses on visualizing
data and creating, managing, and customizing dashboards. Grafana also offers
tutorials in both text and video formats.
## 8. Team management: Grafana wins
Grafana is the only one with team management functionalities in this comparison.
It allows you to create multiple users with different roles, such as admin,
editor, and viewer. You can also group users into teams and assign folder and
permissions to teams instead of users. Prometheus does not have similar
functionalities as it solely focuses on data collection.
## 9. Incident management and alerting: tie
Prometheus does not offer complete alert functionality by default. You can set
up alert rules inside the Prometheus server, but the server cannot push the
notification to the necessary channels until you install the
[Alertmanager](https://prometheus.io/docs/alerting/latest/alertmanager/) plugin.
Once it is installed, you can route alerts to email, Slack, and other channels.
Grafana offers a complete alerting service by default. You may set up alert
rules, add labels and notification policies, tell Grafana where, when, and how
the notifications get routed.
[note]
☎ Want to get a call, SMS, or Slack alert when
something goes wrong in Grafana or Prometheus?
Go to
Better Stack Uptime
and set up alerts for your application, services,
and scheduled tasks in under 2 minutes.
[/note]
## 10. Pricing: tie
Finally, regarding pricing, Prometheus is an open-source project that you can
only host on your server. Therefore, the cost depends on how you choose to
deploy it.
You can also self-host Grafana, but it also offers a three-tier commercial plan,
as shown in the image below:
## The ultimate monitoring and alerting setup: Prometheus + Better Stack
Prometheus is excellent at collecting time series data, but turning that data into something your team can act on (reliably, quickly, and without a pile of config files) often becomes the hard part.
If you want a smoother setup for **monitoring, alerting, dashboards, and incident response**, you can keep Prometheus for data acquisition and pair it with **[Better Stack](https://betterstack.com/uptime)** for everything that happens after a signal is created.
Here’s a quick look at what the “monitoring experience” feels like in practice:
With Better Stack in place, you can cover the full workflow end to end:
### Uptime monitoring with no agents and no false positives
Better Stack can monitor your application endpoints directly using fast global checks, and when something fails it captures the context you actually need: **error details, screenshots, and a second-by-second timeline**.
This is often the fastest way to catch real user-facing downtime, even if you already have metrics and alerts elsewhere.
### On-call scheduling and escalations that are easy to manage
Instead of wiring routing rules across multiple tools, Better Stack gives you a single place to define who gets alerted, when, and how (phone calls, SMS, Slack, push notifications, and more).
This demo page is a good overview of what on-call looks like in Better Stack:
### Incident management built around real troubleshooting
Once an incident is triggered, Better Stack helps you keep the event clean and actionable: reduce noise through incident merging, coordinate response, and document what happened.
If you want to see the full lifecycle (from “something is broken” to “post-mortem”), this is the best starting point:
### Prometheus Alertmanager integration without rebuilding your alerting setup
If you already have Prometheus alert rules, you do not need to throw them away.
You can route Alertmanager events into Better Stack, so alerts become real incidents with proper escalation and ownership, instead of “just another notification.”
Better Stack’s on-call demos also include **handling incidents from Prometheus Alertmanager**, which makes this transition straightforward.
### Dashboards built in, so Grafana becomes optional
Better Stack includes **built-in dashboards**, so you can visualise and explore metrics in the same platform where you handle alerts and incidents. You can build charts using SQL, simplified PromQL, and drag-and-drop, and you can even turn logs into metrics when you need a quick signal without writing instrumentation code.
Here’s the dashboards overview:
### Optional, but powerful: live tail for fast debugging
When something goes wrong, dashboards tell you **what** changed, but logs tell you **why**.
If you want the fastest feedback loop during incidents, live tail is one of the most useful tools to keep open while debugging:
## Final thoughts: better together
Prometheus is still one of the best tools for collecting and querying time series data, especially when you want full control over how metrics are produced.
But once you need to operationalise that data (uptime checks, dashboards, alert routing, on-call schedules, incident timelines, and stakeholder updates), Better Stack gives you a cleaner workflow with far less glue code.
If you want a setup that stays simple as your team grows, **Prometheus + Better Stack** is a very practical combination.
Thanks for reading!