Exploring Evidence.dev, Streamlit & Visivo

Evidence.dev vs. Streamlit vs. Visivo

Compare key features, capabilities, and differentiators between Evidence.dev, Streamlit, 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.devStreamlitVisivo
Deployment ModelSelf-host (static site), Self-host (server), Vercel/Netlify deploymentOpen-source (Python library), Self-hosted server, Streamlit Cloud, Snowflake-managed enterpriseOpen-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.)Open-source (Apache 2.0); Free community hosting (limited), Snowflake-managed enterprise hostingOpen 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

Streamlit

Data scientistsPython developersML engineers

Visivo

Analytics EngineersData teamsBusiness usersEngineers

Ease of Development & Deployment

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

Evidence.dev

3/5

Streamlit

5/5

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

Streamlit

Python data science librariesSQL databasesSnowflake native integration

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.

Streamlit

Not a traditional BI dashboard tool – rather, a Python app framework. You write Python to output charts, tables, and UI widgets. Highly flexible (use any Python viz library like Altair, Plotly, etc.), but all customization is via code.

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.

Streamlit

Super easy and fast to turn a Python script into a shareable web app. Perfect for quickly prototyping data apps and internal tools.
Not aimed at non-coders – lack of GUI means business users won't build in it. No built-in multi-user management or security layers (rely on external auth if needed).

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).

Streamlit

DB Access: Yes, if app connects to a DB, it uses direct credentials (no abstraction). Virtualization: No, Streamlit just runs code – any virtualization must be coded. Push: No – app pulls data or receives via API. Other: Security depends on deployment (can use authentication proxies or Snowflake's SSO when integrated). No built-in row-level security – must code filters per user if needed.

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
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Jared Jesionek (co-founder)
Jared Jesionek (co-founder)
Jared Jesionek (co-founder)
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How can I help? This connects to our slack so I'll respond real quickly 😄
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