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put privacy-first web and product analytics on your own stack

OSS scale score Not calculatedOSS health 100
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OSS scale score is an unbounded metric that log-compresses and weights Stars, Watchers, Forks, and Contributors. Discovery score is the current OSS scale score minus the score at discovery. Update pace is commits in the last 30 days, growth momentum is the OSS scale score difference within the recent observation window, and OSS health is a 0–100 rating based on available recency, Community Health, and release data.

Stars
1,166
Primary language
TypeScript
License
AGPL-3.0
Repository last updated
Sep 30, 2026
On this page

Overview

Databuddy analyzes acquisition, behavior, and drop-off for websites and products. In self-host mode, events are written directly to ClickHouse while hosted billing and Databuddy's own telemetry are disabled.

Features and best fit

Based on official documentation; not hands-on tested · Content checked:

Key features

Analyze user journeys and product behavior

Traffic sources, events, funnels, and drop-off patterns support product and website improvement decisions.

Sources: [2]

Run a stack built around PostgreSQL, ClickHouse, and Redis

The dashboard and API sit alongside an event collector, uptime worker, and other services, with analytics events stored in ClickHouse.

Sources: [2][3]

Best fit

Fits teams that want analytics data under their own operational control

SELFHOST=true disables hosted billing and Databuddy telemetry, making the project relevant when analytics infrastructure and data should remain organization-controlled.

Sources: [2]

Before adoption

The production self-host release is not ready yet

The README currently says no release containing the required databuddy-init image has been published, so the release state should be rechecked before production self-hosting.

Sources: [2][4]

Manage application secrets and database credentials separately

Self-hosted and development setups require PostgreSQL, ClickHouse, and Redis passwords plus distinct random BETTER_AUTH_SECRET and DATABUDDY_ENCRYPTION_KEY values.

Sources: [2][3]

Official sources

  1. [1]databuddy-analytics/Databuddy repository(2026-09-30)
  2. [2]Databuddy README(2026-09-30)
  3. [3]Databuddy contributor setup(2026-09-30)
  4. [4]Databuddy v0.0.1 release(2026-09-30)
  5. [5]Databuddy AGPL-3.0 license(2026-09-30)
Supplemental curator note

Databuddy is an AGPL-3.0 privacy-first web and product analytics platform. The repository contains self-hosting code and Docker Compose configuration, but its README currently states that no release with the required databuddy-init image has been published yet. For evaluation, the contributor local-development flow is therefore more realistic than the production self-hosting procedure. The packages/scan component is MIT-licensed.

Try it in 3 steps

  1. 1

    Get the source

    git clone --depth 1 https://github.com/databuddy-analytics/Databuddy.git
  2. 2

    Enter the repository

    cd Databuddy
  3. 3

    Check the official steps

    Continue with the commands in the README Installation, Quick Start, or Getting Started section.

    find . -maxdepth 1 -iname 'README*' -exec sed -n '1,220p' {} \; -quit
Check the official README

Growth

Growth trends · Last 30 days

1,166 Stars

Trend data is still being collected.

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GitHub data

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GitHub Topics

  • alternative
  • analytics
  • europe
  • gdpr
  • gdpr-compliant
  • google-analytics
  • privacy
  • web-analytics
Stars
1,166
Forks
219
Watchers
3
Open issues
32
Owner type
Organization
Primary language
TypeScript
License
AGPL-3.0
Repository last updated
Sep 30, 2026
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