Grafana vs Prometheus
Side-by-side comparison of features, pricing, ratings, and alternatives.
Grafana is a multi-platform open source analytics and interactive visualization web application. It provides charts, graphs, and alerts for the web when connected to supported data sources. A feature-rich platform for building dashboards and visualizing time-series data.
Prometheus is a free software application used for event monitoring and alerting. It records real-time metrics in a time series database (allowing for high dimensionality) built using a HTTP pull model, with flexible queries and real-time alerting. The project is written in Go and licensed under the Apache 2 license, with source code available on GitHub.
- Highly customizable and extensible
- Supports multiple data sources and plugins
- Real-time data streaming and alerting capabilities
- Large community of developers and users
- Highly scalable and performant
- Flexible query language and data model
- Real-time alerting and notification system
- Large ecosystem of integrations and community support
- Steep learning curve for beginners
- Can be resource-intensive for large-scale deployments
- Limited support for certain data sources and plugins
- Steep learning curve due to complex query language and data model
- Requires significant resources and infrastructure to deploy and manage
- Limited support for historical data and long-term storage
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View all →The Verdict
AI-generated from listing dataGrafana offers a richer, customizable visualization layer with multi‑source dashboards, while Prometheus provides the core time‑series storage and alerting engine; choose Grafana for UI‑centric monitoring, Prometheus for raw metrics collection.
Key differences
- •Grafana focuses on dashboard creation and visualizations; Prometheus is a time‑series database and alerting engine.
- •Grafana supports many data sources (Prometheus, Graphite, Elasticsearch, etc.); Prometheus primarily stores its own metrics.
- •Grafana includes built‑in multi‑tenant UI and plugin ecosystem; Prometheus relies on external tools for UI and extensions.
- •Prometheus offers a powerful query language (PromQL) and native alert manager; Grafana consumes alerts but does not provide its own query engine.
- •Grafana’s resource usage can be high for large dashboards; Prometheus requires significant infrastructure for high‑volume metric ingestion.
Pricing & value
Both are free open‑source tools; value depends on whether you need visualization (Grafana) or metric storage (Prometheus).
Ease of use / learning curve
Grafana’s UI is intuitive for dashboard building, though overall setup can be steep; Prometheus’ PromQL is complex for newcomers.
Features & depth
Grafana provides extensive visualizations, plugins, multi‑tenancy, and auth methods; Prometheus focuses on data model and alerting.
Integrations & ecosystem
Both have strong ecosystems: Grafana integrates with many sources; Prometheus integrates with Kubernetes, Docker, and Grafana.
Collaboration
Grafana supports multi‑tenancy and role‑based access via OAuth/LDAP, enabling shared dashboards across teams.
Scalability
Prometheus is designed for high‑performance metric ingestion and fault‑tolerant architecture; Grafana can be resource‑intensive at scale.
Support
Grafana offers email, community forum, and documentation; Prometheus only lists community support and documentation.
Choose Grafana if…
Teams needing unified, customizable dashboards across many data sources and collaborative UI.
Choose Prometheus if…
Teams that require a robust, scalable time‑series store and native alerting for metric‑heavy workloads.
Common questions
Do I need to pay for either tool?
Both Grafana and Prometheus are free open‑source products; no licensing fees are required.
Can Grafana replace Prometheus for metric collection?
No; Grafana visualizes data but does not store metrics. It typically consumes data from Prometheus or other sources.
Which tool offers better built‑in alerting?
Prometheus includes a native alert manager with rule‑based alerts; Grafana relies on alerts from its data sources.