Evidence vs Lightdash
Both are alternatives to Tableau. Here's how they stack up — verified facts, no spin.
Also searched as Lightdash vs Evidence — same comparison, one verdict.
Evidence
Dashboards as Markdown and SQL, versioned in Git.
Evidence takes a genuinely different position: a report is a Markdown file with SQL in it, built into a static site. That means dashboards live in your repository, get reviewed in pull requests, deploy through CI and cannot be silently edited by someone in a UI. MIT licensed. It is the wrong tool for exploratory analysis and the right one for recurring, trusted reporting that has to be identical every month. Included because the BI category assumes a GUI is a requirement and for a good number of engineering teams it is the opposite.
Lightdash
BI that reads your dbt models, so metrics are defined once.
Lightdash builds its entire semantic layer from your existing dbt project: define a metric once in dbt, and it appears in BI with the same definition everywhere. That solves the specific and expensive problem of the same number meaning three different things in three dashboards, which is where most BI trust breaks down. Around 6k stars — the smallest here — and it only makes sense if you already run dbt. Where you do, it is the tightest fit on this page.
Side by side
| Evidence | Lightdash | |
|---|---|---|
| Sovereignty Score | 94 | 87 |
| Open source | Yes | Yes |
| Self-hostable | Yes | Yes |
| Local-first | Yes | Yes |
| License | MIT | MIT (open core; paid cloud tier) |
| Pricing | Free and open source. Evidence Cloud is an optional paid hosted tier. | Open-source core free and self-hostable. Lightdash Cloud is paid. |
Evidence edges it on the Sovereignty Score, but the right pick depends on the trade-offs below.
Evidence
Strengths
- +Reports live in Git — reviewed, versioned, deployable through CI
- +MIT with no enterprise carve-out
- +Output is a static site: fast, cheap, nothing to keep running
- +Impossible to quietly alter a number without a commit
Trade-offs
- −No point-and-click building — you write SQL and Markdown
- −Not an exploration tool; it produces fixed reports
- −Non-technical staff cannot author
- −Small community
Lightdash
Strengths
- +Metrics defined once in dbt and used everywhere — no drifting definitions
- +Version-controlled BI, reviewed in pull requests like code
- +MIT core
- +Fast to adopt if dbt is already in place
Trade-offs
- −Effectively requires dbt — useless without it
- −Smallest project and community on this page
- −Fewer visualisation types than Superset
- −Less suited to ad-hoc exploration by non-technical staff
Related alternative guides
Facts verified 2026-08-04. Licenses and pricing change — spotted something out of date? That's a correction we want.