Exploring Evidence.dev, Grafana & Visivo

Evidence.dev vs. Grafana vs. Visivo

Compare key features, capabilities, and differentiators between Evidence.dev, Grafana, Visivo. This comprehensive analysis will help you make an informed decision for your data visualization needs.

Quick Comparison

Key features and capabilities at a glance

FeatureEvidence.devGrafanaVisivo
Deployment ModelSelf-host (static site), Self-host (server), Vercel/Netlify deploymentOpen-source (AGPLv3), Grafana Enterprise, Grafana Cloud, Self-hostedOpen-source, Cloud Service, Self-hosted
PricingOpen-source (MIT); free to use. New hosted service as of fall 2024 (can also deploy on Vercel, Netlify, etc.)OSS free; Grafana Enterprise (paid add-ons); Grafana Cloud (free tier & paid).Open source (GPL-3.0)
Cost$$$$
Git Integration
CI/CD & Testing
Real-time
AI Features
Visual to Code
DAG-Based

Target Users & Use-Cases

Each BI tool is designed with specific user personas in mind.

Evidence.dev

Analytics engineersData-savvy users who prefer code/markdown workflowEngineers & Academics

Grafana

DevOps engineersIT monitoring teamsData engineers for time-series analytics

Visivo

Analytics EngineersData teamsBusiness usersEngineers

Ease of Development & Deployment

Development experience directly impacts team productivity and time-to-value.

Evidence.dev

3/5

Grafana

3/5

Visivo

5/5

Key Integrations & Ecosystem

A robust ecosystem of integrations is essential for modern BI tools.

Evidence.dev

SQL databases via JDBC/ODBCdbt metadata integrationStatic site deployment platforms

Grafana

Time-series databases (Prometheus, InfluxDB)SQL databases and cloud metricsAlerting systems (PagerDuty, Slack)

Visivo

dbt coreAll major databasesCustom connector frameworkSlack for alertsGithub

Visualization Capabilities

The ability to create compelling visualizations is key to data storytelling.

Evidence.dev

Reports built as Markdown with embedded SQL and charts. Outputs static HTML dashboards. Customization via editing Markdown/HTML/CSS; not a point-and-click UI.

Grafana

Optimized for time-series and metrics visualizations (graphs, gauges, alerts). Supports logs and traces panels too. Basic charts for category data exist but not Grafana's strong suit. Highly customizable dashboards via JSON config or UI. Many community panels (plugins) to extend visualization types.

Visivo

Highly custom UI with easy defaults

Detailed Differentiators

Each platform's unique strengths and limitations.

Evidence.dev

+ Write dashboards as code – lightweight, reproducible, easily integrated with dbt pipelines. Great for data narratives that combine text, data, and charts.
Static output means no ad-hoc drilling by end users; requires comfort with writing Markdown/SQL.

Grafana

Best for operational dashboards – combining metrics, logs, and traces in one UI (especially with Grafana Cloud). Very extensible via plugins.
Not designed for ad-hoc business analytics on arbitrary data – e.g., no built-in SQL query builder for relational data (user must write queries or use other tools to prepare data). Visualizations not as geared for presentation (more for investigation).

Visivo

BI-as-code approach enables version control, collaboration, and CI/CD workflows. DAG-based architecture provides powerful data transformation capabilities and dependency management. Seamless visual-to-code workflow allows both technical and non-technical users to build dashboards effectively.
Requires understanding of data concepts; not a pure drag-and-drop tool like Tableau. Initial setup requires technical knowledge for optimal configuration.

Security & Architecture

Critical considerations for enterprise deployments.

Evidence.dev

DB Access: Queries run at build time (or page load if in server mode); not needed for end viewer (static pages). Virtualization: By nature, it materializes results into the page (no live DB query once published). Push: Yes – essentially a push of data into static site. Other: No runtime user management (pages are static); security depends on where you host (you wouldn't include sensitive data in a public build).

Grafana

DB Access: Yes, connects directly to data sources (or through its agents). Virtualization: More like federation – it queries multiple backends via plugins. Push: Metric data is often pushed into time-series DBs which Grafana then reads – so indirectly yes (in monitoring use-cases). Grafana itself pulls from those DBs. Other: Auth via LDAP/OAuth. Granular permissions on dashboards and data sources. Encryption and other enterprise security features in paid version.

Visivo

No db access required. Very strong security features due to the DAG-based access controls and the push based deployment model.

Why Visivo Stands Out

While each platform has its strengths, Visivo offers unique advantages for modern data teams.

DAG-Based Architecture for complex data transformations
Visual to Human-readable Code conversion
Multiple development approaches for all skill levels
AI-Powered dashboard creation
Full Git integration and version control
Open-source with enterprise features

Ready to Experience Modern BI?

Try Visivo today and see how it transforms your data analytics workflow.

$ curl -fsSL https://visivo.sh | bash
undefined
Jared Jesionek (co-founder)
Jared Jesionek (co-founder)
Jared Jesionek (co-founder)
agent avatar
How can I help? This connects to our slack so I'll respond real quickly 😄
Powered by Chatlio