Grafana is a powerful tool for analyzing and visualizing data. It requires the data to be stored in or streamed from a separate location for access and display. These storage locations or streams are called data sources, and a Grafana data source refers to any database or stream that Grafana can connect to and retrieve data from for visualization. Grafana can produce charts, graphs, and alerts for the web when connected to supported data sources.
Grafana is owned by Grafana Labs, a company founded by Torkel Ödegaard, Anthony Woods, and Raj Dutt in 2014. It develops and maintains Grafana as an open-source data visualization and monitoring tool. Grafana has received significant VC investments – see: Grafana Labs announces $240 million Series D round led by GIC and welcomes new investor J.P. Morgan | Grafana Labs.
Grafana Open Source is free. The core version of Grafana is completely free and open source. This version is self-hosted and requires you to host and manage it yourself, typically on your own servers or infrastructure.
Many organizations find they need to upgrade to the supported paid for on-prem offering of “Grafana Enterprise” to access essential features and support.
Grafana Cloud offers a free tier within its hosted services - “Grafana Cloud Free Tier”. This version is hosted and managed by Grafana Labs, so you don’t have to worry about infrastructure management. However, this free tier comes with many restrictions that make it unsuitable for many to use. There are usage limitations such as:
In practice, many organizations find that they need to upgrade to one of the higher tiers of the hosted service. Details of premium offerings, pricing and feature matrices are available, here: Grafana Pricing | Free, Pro, Advanced, Enterprise.
Some popular data sources that Grafana supports, include:
These data sources provide a variety of options for monitoring, metrics collection, and log analysis.
Grafana originally targeted time series databases such as InfluxDB and Prometheus but has evolved to support relational databases such as MySQL, MariaDB, PostgreSQL and Microsoft SQL Server.
Information on supported data sources (and customized plugins for other sources) can be found in the Grafana documentation, see: Data sources | Grafana documentation.
Prometheus and Grafana serve different purposes, so the question isn’t about which is better, but how they complement each other. Prometheus is a monitoring and alerting tool focused on collecting, storing, and querying time-series data. It scrapes metrics from applications, stores them, and uses PromQL for querying and analysis. It also includes alerting capabilities, making it an option for monitoring the performance and availability of applications, services, and infrastructure.
Grafana, on the other hand, is a visualization and analytics platform designed to display data and create dashboards. It doesn’t collect data itself but pulls data from other sources such as Prometheus, InfluxDB, Elasticsearch, and more. Grafana’s strength is its ability to create interactive, user-friendly dashboards for interpreting metrics visually, making it suitable for centralized overview and insights.
Prometheus is best used when you need a solution for collecting and alerting based on metrics, while Grafana is the choice for visualizing data from multiple sources. They are commonly used together: Prometheus handles the back-end data collection, and Grafana connects to it for visualization. This combination provides a solution of sorts, combining both monitoring (with alerting) and data display.
Prometheus and Grafana aren’t directly comparable as one being better than the other; they serve different roles in a monitoring stack. Generally, Grafana will need to be combined with something like Prometheus along with some other tooling (Jaeger for tracing) to build a more complete monitoring solution. Of course, this approach involves the use of multiple consoles and blind spots with a lack of correlation between systems that is available within unified AIOps platforms.
Prometheus and Grafana offer an open-source monitoring solution that is suitable for teams needing flexibility and customization. Prometheus handles metrics collection and storage, while Grafana provides visualization and dashboarding capabilities. This stack is cost-effective and can work well for organizations with the technical skills to manage deployment, scaling, and integration with additional tools for logs and tracing (e.g., Loki, Jaeger). However, it requires ongoing maintenance and manual configuration to scale effectively, particularly in large or complex environments.
eG Enterprise, in contrast, offers a fully supported commercial solution designed to provide an all-in-one monitoring solution. eG Enterprise covers metrics, logs, traces, real user monitoring (RUM), synthetic monitoring and more in a single package. It is easy to set up, scales automatically, and comes with advanced features like AIOps-powered anomaly detection and automated root cause analysis.
eG Enterprise automatically discovers applications, services, dependencies, and network relationships in real-time. It provides detailed maps and dependency views without needing additional setup. In contrast, Grafana requires you to build these views manually using metrics and visualizations, which can be time-consuming and less precise. In modern application architectures involving auto-scaling Grafana may not be an optimal choice.
eG Enterprise is ideal for organizations that want fast deployment and comprehensive observability with minimal effort. eG Enterprise is also designed to give monitoring, reporting and troubleshooting capabilities to the whole organization rather than just dedicated technical staff.
Overall, Prometheus and Grafana are great for cost-sensitive, technically capable teams needing a highly customizable solution, while eG Enterprise is suited to those prioritizing ease of use, maintainability, scalability, and advanced monitoring capabilities in a unified, managed platform.
