Redash vs Grafana

Side-by-side — pricing, strengths, tradeoffs, and fit.

Redash

Connect to any data source and visualize your data easily.

Grafana

Multi-platform analytics and visualization web application.

At a glance

Open SourceFree Tier
● Established·From $0
Open SourceFree Tier
● Established·From Freemium

Overview

One-liner

Connect to any data source and visualize your data easily.

One-liner

Multi-platform analytics and visualization web application.

Maturity

Established

Maturity

Established

Open source

✓ Yes

Open source

✓ Yes

Pricing

Free tier

✓ Available

Open source — free to use

Free tier

✓ Available

Starts at

$0

Starts at

Freemium

Model

Flat rate

Model

Flat rate

Enterprise

✕ None

Enterprise

✕ None

Best for

✓ Best for

Data teams who need to connect multiple data sources and create interactive dashboards.
Companies looking for a self-hosted solution with extensive customization options.
Organizations that require real-time monitoring of KPIs through customizable alerts.

✓ Best for

Teams needing comprehensive monitoring and visualization capabilities across multiple data sources.
Organizations that require customizable dashboards to track various metrics in real-time.

Not ideal for

✕ Not for

Teams requiring cloud-based managed services without the need for self-hosting.
Projects needing advanced AI-driven analytics beyond basic querying and visualization.

✕ Not for

Projects with very limited budget as the enterprise features are paid.
Users who prefer a cloud-hosted solution without self-management overhead.

Strengths

↑ Strengths

Connects to multiple data sources including SQL databases, Google Sheets, and more.
Provides a web-based interface for creating visualizations and dashboards.
Supports sharing of queries and dashboards with team members or the public.
Includes alerting features based on query results.

↑ Strengths

Customizable dashboards and visualizations
Real-time data monitoring
Alerting and notifications
Extensive plugin ecosystem

Weaknesses

↓ Weaknesses

Limited built-in support for advanced analytics and machine learning
Performance issues under heavy load
Documentation can be sparse and out-of-date

↓ Weaknesses

Steep learning curve for new users
Limited native support for certain data sources
Performance issues with large datasets
Complex setup for advanced use cases
Full Redash profile →Full Grafana profile →