Best Open Source Analytics
Understanding how users interact with your product is fundamental to making good decisions — about which features to build, where friction exists, and what's actually driving growth. Analytics tooling has become ubiquitous, but the way most teams implement it creates a quiet tension between insight and privacy. Every pageview, click, and scroll event sent to a third-party analytics service is data about your users that lives on someone else's infrastructure.
The Open Source Vanguard
Apache Superset
Enterprise-ready business intelligence web application.
ClickHouse
Column-oriented database management system for generating analytical data reports in real-time, optimized for performance with a C++ core.
Metabase
The simplest, fastest way to get business intelligence and analytics throughout your company.
PostHog
🦔 PostHog is an all-in-one developer platform for building successful products. We offer product analytics, web analytics, session replay, error tracking, feature flags, experimentation, surveys, data warehouse, a CDP, and an AI product assistant to help debug your code, ship features faster, and keep all your usage and customer data in one stack.
Plausible
Simple, open source, lightweight and privacy-friendly web analytics alternative to Google Analytics.
Matomo
Empowering People Ethically 🚀 — Matomo is hiring! Join us → https://matomo.org/jobs Matomo is the leading open-source alternative to Google Analytics, giving you complete control and built-in privacy. Easily collect, visualise, and analyse data from websites & apps. Star us on GitHub ⭐️ – Pull Requests welcome!
DAC
Dashboard-as-code tool that defines dashboards in YAML and TSX, with a built-in semantic layer.
Proprietary Giants
The closed-source benchmarks for these open-source alternatives.
Google Analytics dominated this space for over a decade by being free and comprehensive. But the shift to GA4, growing regulatory pressure from GDPR and CCPA, and increasing user awareness of tracking have created an opening for alternatives that respect privacy by default. The question has moved from 'Should we track user behavior?' to 'Can we understand our users without compromising their privacy?'
The answer, increasingly, is yes. Privacy-first analytics platforms — both commercial and open-source — have proven that you can get actionable insights from aggregate data without building individual user profiles, dropping cookies, or sending behavioral data to third-party ad networks. For many teams, the switch isn't just about compliance; it's about building trust with users who are increasingly aware of how their data is being used.