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Open-Source DevOps · evidence-dev

evidence

Evidence is an open-source BI tool that lets you build interactive dashboards and reports by writing SQL queries and markdown. Instead of drag-and-drop UI, you code your analytics in version-controlled files and deploy as static sites.

Source: GitHub — github.com/evidence-dev/evidence
6.5k
GitHub stars
370
Forks
JavaScript
Primary language
MIT
License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

FieldValue
Repositoryevidence-dev/evidence
Ownerevidence-dev
Primary languageJavaScript
LicenseMIT — OSI-approved
Stars6.5k
Forks370
Open issues267
Latest release@evidence-dev/[email protected] (2026-02-06)
Last updated2026-02-18
Sourcehttps://github.com/evidence-dev/evidence

What evidence is

JavaScript-based framework that executes SQL queries embedded in markdown, renders Svelte components with Tailwind styling, and compiles to static HTML/JS for deployment. Supports templating, conditionals, and loops for dynamic report generation from multiple data sources.

Quickstart

Get the evidence source

Clone the repository and explore it locally.

terminalbash
git clone https://github.com/evidence-dev/evidence.gitcd evidence# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Self-hosted analytics for teams with SQL fluency

Teams comfortable writing SQL can rapidly build custom dashboards version-controlled in Git, avoiding vendor lock-in and SaaS licensing. Works well for orgs needing full control over data and deployment infrastructure.

dbt-integrated data pipeline reporting

Pairs naturally with dbt workflows; queries dbt-transformed tables directly and regenerates reports as data updates, enabling CI/CD-driven analytics.

Lightweight, embedded BI for product teams

Deploy as static sites or embed in existing web apps; low operational overhead and fast iteration cycles for product analytics and exploratory analysis.

Implementation considerations

  • Requires SQL expertise on the team; markdown-only approach has low barrier but scales with data complexity.
  • Static site deployment model suits CI/CD workflows but means reports refresh on schedule, not on-demand.
  • State management and local caching via WebAssembly (DuckDB) reduces backend load; evaluate data size limits for client-side processing.
  • VSCode extension and CLI tooling are the primary development experience; ensure editor familiarity across team.
  • Deployment targets include Netlify, Vercel, and self-hosted; evaluate cost and infrastructure complexity for your scale.

When to avoid it — and what to weigh

  • Business users need no-code dashboarding — Evidence requires SQL and markdown literacy. Teams relying on drag-and-drop BI tools or non-technical stakeholders will face friction.
  • Real-time operational dashboards required — Static site generation and batch query execution do not support true real-time streaming updates or sub-second latency requirements.
  • Complex row-level security or multi-tenancy — No clear indication of built-in RBAC, column-level masking, or multi-tenant isolation. Custom logic would be required and is not documented.
  • Proprietary data connector ecosystem needed — Support for enterprise data sources (e.g., Salesforce, SAP) is not mentioned. Likely limited to SQL databases and dbt, requiring custom adapters for others.

License & commercial use

Evidence is licensed under the MIT License, an OSI-approved permissive license allowing commercial use, modification, and distribution with minimal restrictions.

MIT license permits commercial use without royalty or proprietary requirements. You may build commercial products on top of Evidence and modify it freely. No explicit patent grant or indemnification provided by MIT; standard commercial risk assessment applies. Verify compatibility with your organization's compliance requirements.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

SignalAssessment
MaintenanceActive
DocumentationAdequate
License clarityClear
Deployment complexityLow
DEV.co fitGood
Assessment confidenceHigh
Security considerations

Static site deployment reduces attack surface compared to traditional server-based BI tools. Data queries execute against your own data sources; no data leaves your infrastructure by default. Key considerations: encryption of credentials for database connections, access control over markdown/report files in Git, no apparent built-in RBAC or row-level security for published reports (likely require external auth layer), and WebAssembly/DuckDB client-side processing—verify data sensitivity policies for in-browser computation. Requires careful review of deployment environment security.

Alternatives to consider

Metabase

Drag-and-drop, self-hosted open-source BI with native RBAC and broader data connector support; better for non-technical users but more operational overhead.

Superset

Open-source visualization platform with similar self-hosted model and SQL queryability; larger ecosystem but steeper deployment complexity.

Grafana + Loki/Prometheus

Time-series and observability focus with templating and alerting; better for ops/monitoring than business analytics but highly automated infrastructure-native.

Software development agency

Build on evidence with DEV.co software developers

Review the full documentation at docs.evidence.dev, test the VSCode extension, and assess SQL expertise and deployment infrastructure fit with your org. Contact the community on Slack for production deployment patterns.

Talk to DEV.co

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evidence FAQ

Can I query real-time data or must I batch refresh reports?
Evidence compiles reports to static sites. Refresh frequency depends on your deployment CI/CD trigger (e.g., scheduled, on data change). True real-time streaming is not supported; this is a batch analytics tool.
Does Evidence enforce security rules like row-level access control?
Not clearly documented. Evidence focuses on query and visualization logic. You must layer authentication (e.g., OAuth, basic auth) in your deployment environment or web server to control report access.
What data sources does Evidence support?
Any SQL-queryable database and dbt-transformed tables. Specific connectors not detailed in README; review docs.evidence.dev for full list and version compatibility.
Is Evidence suitable for embedding in a larger product?
Possible. Evidence generates static HTML/JS and components can be embedded. Custom integration and API surface for external apps requires further investigation.

Custom software development services

Need help beyond evaluating evidence? DEV.co is a software development agency offering software development services and web development for teams of every size. Our software developers and web developers build custom software, web applications, APIs, and open-source devops integrations — and maintain them long-term.

Ready to evaluate Evidence for your team?

Review the full documentation at docs.evidence.dev, test the VSCode extension, and assess SQL expertise and deployment infrastructure fit with your org. Contact the community on Slack for production deployment patterns.