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 through its custom query language, which allows you to select and aggregate time-series data. The collected metrics 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

✔ - 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 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.

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.

4. Easy installation and deployment: Grafana wins

Prometheus is easy enough to setup as all you need to do is download the appropriate binary for your operating system and execute it. Official Docker images are also available for all Prometheus services.

Self-hosting Grafana is also quite easy as a multitude of options 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 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 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.

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 + Grafana + Better Stack

When it comes to alerting and incident management, both Prometheus and Grafana require a lot of configurations. If you are looking for something more intuitive and easier to set up, take a look at Better Stack Uptime. It is a monitoring and incident management platform that can monitor your application's status directly, with no installation required, and it will send you alerts if something goes wrong.

When you set up a monitor for your application, Better Stack Uptime allows you to create alerts. For example, you can ask Better Stack Uptime to call, send SMS, email, or push notifications to the current on-call person if an incident happens.

When you integrate Better Stack Uptime with Prometheus, Better Stack Uptime will replace the default Alertmanager. All you need to do is locate Alertmanager's configuration file and replace its content with the sample provided on the instruction page.

If you wish to integrate Better Stack Uptime with Grafana, choose Connect Grafana to Better Stack Uptime and follow the instructions to create a webhook. The webhook will channel all your Grafana alerts to Better Stack Uptime instead.

It doesn't matter which integration you choose to use, Better Stack Uptime allows you to use the full power of its on-call schedule and team management functionalities and it will let you decide how you wish to be notified when an incident occurs.

Final thoughts: better together

Prometheus and Grafana are both great observability solutions. However, they were created with different priorities. Prometheus focuses on data acquisition, allowing users to select and aggregate time series data in real time. Grafana, on the other hand, focuses on data visualization. We can't really say one is better than the other, but in fact, they work best when they work together.

Thanks for reading!

Article by

Eric Hu

Eric is a technical writer with a passion for writing and coding, mainly in Python and PHP. He loves transforming complex technical concepts into accessible content, solidifying understanding while sharing his own perspective. He wishes his content can be of assistance to as many people as possible.

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