Evidence.dev: SQL Based Analytics and Dashboards

Evidence.dev: SQL Based Analytics and Dashboards Review: Features, Pricing, and Why Startups Use It

Introduction

Evidence.dev is an open-source, code-first analytics and dashboarding tool that lets teams build data reports using SQL, Markdown, and simple components instead of drag-and-drop interfaces. It sits at the intersection of business intelligence (BI), analytics engineering, and documentation.

Startups use Evidence.dev because it fits naturally into their existing developer-centric workflows: everything lives in Git, changes go through pull requests, and the logic is expressed in SQL rather than hidden in proprietary visual tools. For lean teams without a full BI department, this approach offers more transparency, reproducibility, and control at a lower cost than traditional BI platforms.

What the Tool Does

Evidence.dev’s core purpose is to turn SQL queries into production-ready reports and dashboards that can be shared across the company or with customers.

At a high level, Evidence.dev allows you to:

• Connect to your data warehouse (e.g., Snowflake, BigQuery, Postgres, etc.).
• Write SQL queries to define datasets.
• Embed those results into pages using Markdown and components (charts, tables, KPIs).
• Publish dashboards as static or server-rendered web pages.
• Manage everything via Git, with version control and CI/CD.

Instead of “clicking around” in a BI tool, your analytics become part of your codebase. This is especially attractive to startups that already use modern data stacks and treat analytics as code.

Key Features

1. SQL-First Workflow

Evidence.dev is built around SQL files that define queries for each page or component. There’s no proprietary query builder; what you see is what you get in SQL.

• Direct SQL control: You can leverage CTEs, window functions, and joins exactly as you would in your warehouse.
• Reuse logic: Shared queries and models can be reused across multiple dashboards.
• No vendor lock-in: Your analytical logic is plain text in your repo, not locked in a database UI.

2. Markdown-Driven Reporting

Reports are written as Markdown files that include SQL query references and components. This makes it easy to combine narrative explanations with data visualizations.

• Data storytelling: Blend charts, tables, and narrative text in one place.
• Developer-friendly: Similar to writing documentation; non-technical contributors can still edit text.
• Versioned content: Every change to wording or logic is tracked in Git.

3. Built-In Visual Components

Evidence.dev includes a library of components that render data from your SQL queries:

• Charts: Line, bar, area, scatter, and other basic chart types.
• Tables: Paginated tables, sortable columns, and basic formatting.
• KPIs: Single-number highlights, comparisons vs previous periods, and trend indicators.
• Filters: Controls like dropdowns or date pickers to allow users to interact with the data.

These components are defined declaratively in your Markdown, referencing query results by name.

4. Git-Based Collaboration and CI/CD

Evidence.dev projects are code repositories. This gives you:

• Pull requests and code review: Data changes are reviewed like any other code change.
• Branch-based previews: Preview environments for new dashboards before merging.
• Rollbacks: Revert to previous versions if a deployment introduces bad logic.

5. Integration with Modern Data Warehouses

Evidence.dev connects directly to:

• Snowflake
• BigQuery
• Postgres and compatible databases
• Other warehouses via supported drivers or connection strings

It assumes you already centralize data in a warehouse, then queries it directly for your dashboards.

6. Developer-Friendly Tech Stack

Evidence.dev is built using familiar web technologies (Svelte and Node under the hood) and is designed to work well with:

• dbt for data modeling and transformation.
• GitHub/GitLab for version control.
• Vercel/Netlify or similar for deployment.

For many startups, it slots neatly into the existing data and engineering workflow.

Use Cases for Startups

1. Internal Product and Growth Analytics

Founders and product teams use Evidence.dev to build self-serve analytics without standing up a heavy BI stack:

• Product usage and activation funnels.
• Feature adoption dashboards by segment.
• Marketing performance and cohort analysis.
• Revenue and subscription metrics (MRR, churn, LTV, ARPU).

2. Executive and Board Reporting

Instead of building static slide decks every month, teams create live dashboards:

• Always up-to-date KPI pages for leadership.
• Board-ready views that can be exported or shared as links.
• Narrative commentary embedded next to charts for context.

3. Customer-Facing Analytics and Portals

B2B startups often need to expose analytics to their customers. Evidence.dev can be used to:

• Build white-labeled analytics portals.
• Provide usage reporting for enterprise clients.
• Deliver data-rich customer success dashboards.

This can be more flexible and cheaper than embedding a large BI tool into your product.

4. Data Team Workflows and Documentation

Data teams use Evidence.dev as a living documentation layer on top of the warehouse:

• Document key metrics and how they’re calculated.
• Create reference dashboards for other teams (sales, CS, marketing).
• Track experiment results and A/B test performance.

Pricing

Evidence.dev is open source, and its pricing model primarily revolves around hosting and team features rather than per-seat BI licenses. The exact specifics may evolve, but broadly it looks like:

Plan	Best For	Key Limits	Notable Features
Open Source / Self-Hosted	Technical teams comfortable managing infrastructure	Infrastructure and maintenance handled by your team	Full control, run in your environment, no license fees
Hosted / Cloud	Startups wanting managed hosting and faster setup	Usage-based limits (projects, users, or runtime) depending on tier	Managed infrastructure, easier deployment, team collaboration tools

Compared to traditional BI platforms, costs are typically lower because:

• There’s no heavy per-seat pricing for viewers.
• You can start with self-hosted and move to managed later.
• You reuse your existing cloud infrastructure if preferred.

Founders should check Evidence.dev’s current pricing page for the latest specifics and any new tiers (such as enterprise features, SSO, or priority support).

Pros and Cons

Pros

Cons

Code-first and SQL-native: Perfect fit for teams that already treat data as code. Transparent and version-controlled: All logic is in Git, reviewable and auditable. Lower cost than traditional BI: Especially for technical teams and self-hosting. Flexible and composable: Easy to extend and integrate with modern data tools. Great for narratives: Combines documentation and analytics elegantly.

Requires SQL skills: Not ideal for teams wanting pure no-code analytics. Setup and DevOps overhead: Self-hosting requires engineering time and infra. Smaller ecosystem: Fewer out-of-the-box integrations compared to legacy BI giants. Feature depth: Advanced features like pixel-perfect dashboards or complex governance may lag established tools. Learning curve for non-engineers: Product or ops folks may need support from data engineers.

Alternatives

Evidence.dev sits alongside several other analytics and BI options. Here’s how it compares conceptually:

Tool	Approach	Best For	Key Difference vs Evidence.dev
Metabase	Open-source BI with GUI query builder	Mixed teams, including non-technical users	More point-and-click; less “analytics as code”; weaker narrative/reporting layer.
Superset	Open-source dashboarding and exploration	Data teams needing traditional dashboards	More like a classic BI tool; less integrated Markdown/report storytelling.
Looker / Looker Studio	Enterprise BI and semantic modeling	Larger companies with formal data teams	Richer governance and semantic modeling but expensive and more complex.
Mode	SQL + notebooks + dashboards	Analytics teams working closely with product	Similar SQL-first ethos, but Evidence.dev is more Git-native and open-source friendly.
Redash	SQL query runner and simple dashboards	Teams wanting lightweight SQL dashboards	Evidence.dev offers a more opinionated “reports as code” model and narrative-driven pages.

Who Should Use It

Evidence.dev is best suited for startups that:

• Already have a data warehouse and write SQL regularly.
• Have at least one data-savvy engineer or analytics engineer on the team.
• Care about version control, reproducibility, and code review for metrics.
• Want to build narrative reports, internal docs, and dashboards in one place.
• Prefer open-source and infrastructure control over black-box SaaS.

It may not be ideal if:

• Your team has very limited technical skills and needs a fully no-code BI tool.
• You want instant drag-and-drop dashboards with minimal setup.
• You require enterprise-grade governance, SSO, or complex permissions out of the box and have budget for a full BI platform.

Key Takeaways

• Evidence.dev is a SQL-first, open-source analytics and reporting tool that turns queries into narrative dashboards.
• It fits especially well in engineering-led startups that already use modern data stacks and Git-based workflows.
• Its strengths are transparency, version control, and cost-efficiency, rather than no-code ease of use.
• For founders and product teams with SQL skills, it can replace heavier BI tools for internal dashboards, board reporting, and even customer-facing analytics.
• Teams without technical capacity or needing advanced enterprise BI features may be better served with alternatives like Metabase, Superset, Mode, or Looker.

For startups that treat analytics as a first-class software product, Evidence.dev is a compelling foundation for building durable, maintainable data reporting without the overhead of traditional BI systems.