Best open-source alternatives to Google Analytics

Umami is a web analytics platform positioned as a simple, fast, privacy-focused alternative to Google Analytics. It is aimed at users who want to self-host their analytics stack and keep control over their data rather than relying on a third-party hosted service. The project can be installed from source or deployed with Docker, and it uses PostgreSQL for storage. The README describes a standard local deployment flow: clone the repository, install dependencies, configure a database connection, build the application, and start the server. It also notes that the build process creates an initial admin user, and that the app can be served behind a reverse proxy or on a chosen port.

Rybbit is an open source web and product analytics platform positioned as a privacy-friendly alternative to Google Analytics. It is designed for teams that want detailed insight into website and product usage without relying on cookies, and it emphasizes quick setup and an intuitive interface. The project supports both hosted use and self-hosting on a VPS, which makes it suitable for organizations that want control over their analytics data. Its interface includes metrics such as sessions, pageviews, bounce rate, session duration, session replays, funnels, retention, custom events, advanced filtering, location maps, and real-time reporting. The README also highlights support for organizations and unlimited sites, indicating a collaborative, multi-site analytics workflow.

Matomo is a free and open source web analytics platform designed for organizations that want to host their own analytics stack and retain control over their data. It is presented as an alternative to Google Analytics and is installed on a customer’s own web server, where it stores tracking data in a local database and serves reports through a web interface. The project is aimed at users who need privacy-conscious, customizable analytics for websites. After installation, Matomo provides a JavaScript tracking tag to add to sites, a modern dashboard for viewing reports, and an extensible plugin architecture for adding or removing functionality. The README also highlights advanced analytics capabilities such as e-commerce, goals, campaigns, segmentation, geolocation, and real-time visits/maps, along with an API for accessing statistics.

GoAccess is an open source web log analyzer built for administrators, DevOps engineers, and security professionals who need fast insight into server activity. It processes access logs in real time and presents statistics in a terminal by default, while also being able to generate a self-contained HTML dashboard for browser viewing. The project is designed to be lightweight and practical: it supports many common log formats, offers incremental processing with on-disk persistence, and can produce JSON and CSV reports for downstream use. It is suitable for quick SSH-based investigations, ongoing traffic monitoring, and spotting suspicious patterns such as brute-force attempts, scanners, and anomalous requests. The README also documents installation across multiple platforms and mentions Docker and docker-compose support for container-based deployment.

GoatCounter is a web analytics platform aimed at people who want simple, privacy-friendly statistics instead of heavier tools like Google Analytics or Matomo. It can be used as a hosted service or self-hosted on a private server, and the README emphasizes that the code is open source and can be run without restrictions. The project is designed for site owners and developers who want to collect meaningful traffic data with minimal overhead. It supports a standard JavaScript snippet, a no-JavaScript image tracker, backend middleware integration through an HTTP/REST API, and importing logs from common web servers and proxies. For self-hosting, it can run with SQLite or PostgreSQL, and the README documents binary releases, Docker, Docker Compose, and source builds.

Plausible Analytics is an open source web analytics platform designed as a privacy-first alternative to Google Analytics. It is intended for website owners and teams that want traffic insights without cookies, personal data collection, or complex reporting interfaces. The project offers a managed cloud service as well as a self-hosted Community Edition. It focuses on lightweight tracking, simple dashboards, and practical metrics such as goals, conversions, revenue attribution, funnels, and real-time traffic. The README also highlights reporting via email or Slack, sharing dashboards publicly, importing historical Google Analytics data, and integrating with Google Search Console. Self-hosters can run their own instance and access raw data directly from ClickHouse.

Countly is a self-hosted analytics and customer engagement platform aimed at organizations that want full control over their data and deployment environment. It is positioned as a privacy-first alternative to SaaS-only analytics tools and can be deployed on-premises or in a private cloud. The repository contains the server-side component used to collect, process, and present analytics data from mobile, web, desktop, and connected-device applications. The platform combines event tracking, crash reporting, push notifications, remote configuration, dashboards, reports, and compliance tooling in one extensible system. It exposes read and write APIs and uses a plugin-based architecture, making it suitable for teams that need customization, integrations, and the ability to extend functionality over time. The README also describes multiple editions, including a free self-hosted Lite plan and enterprise offerings with advanced features and support.

PostHog is a product intelligence platform aimed at teams that want to understand user behavior, diagnose issues, and ship product changes from a single place. It brings together analytics, session replay, observability, surveys, workflows, and AI-assisted tools so users can connect product data with actions and decisions. The project is designed for both cloud usage and self-hosting. The README highlights a recommended cloud offering for quick setup, while also describing an advanced open-source hobby deployment path that can be installed on Linux with Docker. It also supports integration through SDKs, a web snippet, APIs, and an MCP setup for agentic workflows and developer tools.

Medama Analytics is an open-source website analytics project for people and teams that want to track site usage without cookies or invasive identifiers. It emphasizes privacy while still providing useful, real-time visibility into website performance and user interactions. The tracker is described as very lightweight, making it suitable for minimal-impact deployment on websites. The project is designed to be self-hosted and simple to run, with a single-binary setup and no external dependencies. It also exposes an OpenAPI-based server for integration into dashboards or other tooling. The README positions it as a practical analytics solution for small websites and privacy-conscious deployments, including environments with limited resources.

Aptabase is an open-source analytics platform designed for mobile, desktop, and web applications. It positions itself as an alternative to Firebase and Google Analytics, with an emphasis on privacy-first tracking, minimal data collection, and compliance with major privacy regulations. The project provides a central dashboard for viewing key metrics and offers SDKs for a wide range of ecosystems, including Swift, Kotlin, React Native, Flutter, Electron, and more. It is aimed at developers who want application analytics without relying on closed or privacy-invasive tooling. Aptabase can be used through a managed cloud offering or self-hosted on the user’s own servers. The README also highlights that the core server code and SDKs are open source, and that contributors can extend the platform or build additional SDKs for unsupported languages and frameworks.

Bit is a lightweight, self-hosted tracking service focused on collecting minimal request metadata. It is designed for users who want basic analytics-style information such as country, browser, operating system, referer, and forwarded IP details without cookies or persistent tracking beyond what a normal client request provides. The project emphasizes speed, low resource usage, and straightforward deployment. The README highlights Docker, Docker Compose, and Dokku-based installation paths, along with a CLI for creating and managing API keys and users. It appears aimed at self-hosters who want a simple production-ready service with minimal dependencies and a small container footprint.

Swetrix is a self-hostable web analytics platform positioned as a privacy-focused alternative to Google Analytics. It is aimed at site owners and teams who want to understand traffic, performance, sessions, and navigation behavior without relying on cookies or invasive tracking. The README describes a quick self-hosting setup based on cloning the repository, configuring environment variables, and starting the services with Docker Compose. It also points readers to more detailed self-hosted documentation and indicates that the web portal becomes available at the configured base URL after deployment.

Liwan is a web analytics application focused on privacy and simplicity. It is intended for website owners who want to track traffic without cookies, cross-site tracking, or persistent identifiers, while keeping data stored on their own server. The project emphasizes ease of deployment through a single self-contained binary and minimal setup requirements. It offers real-time dashboards, visitor and pageview reporting, referrer insights, and automatic bot filtering, and the README suggests it is lightweight enough to run on modest hardware such as a VPS, a Mac mini, or a Raspberry Pi.

ΛNΛLOG is a minimal analytics application designed to be self-hosted. It presents a dashboard for viewing tracked events and is positioned as a lightweight alternative inspired by piratepx. The project supports several storage backends, including Redis, PostgreSQL, MongoDB, and SQLite, making it adaptable to different deployment environments. It is aimed at developers or site owners who want a simple analytics stack they can run themselves. The README describes local development, deployment on Netlify and Vercel, and containerized deployment with Docker. It also documents a small HTTP API for reading and posting events, plus environment variables for protecting requests and adjusting data-fetching behavior.

Offen Fair Web Analytics is a self-hosted analytics system designed for operators who want insight into website usage without sacrificing user privacy. It emphasizes consent-based tracking, end-to-end encryption, and first-party data handling so that users can review or delete their own data. The project is aimed at teams running one or more websites, and it supports sharing website accounts within teams. Operators integrate a code snippet into their pages, then view aggregated metrics in an auditorium-style interface, while users can inspect their own collected data through the same installation. The README also highlights localization, banner customization, and a lightweight deployment model using a binary or Docker image.

Vince is a self-hosted web analytics application positioned as an alternative to Google Analytics. It is aimed at site owners who want to track traffic and events while keeping their own data, avoiding cookies, and running the system themselves. The project emphasizes simplicity and low operational overhead. It ships as a single binary, can be installed on macOS and Linux with a shell script, and also offers Docker and Helm deployment paths. The README highlights features such as event tracking, page and visit analytics, public dashboards, unique share links, and automatic TLS, while noting that it is intentionally lean and does not aim for full feature parity with Plausible Analytics.

AWStats is a long-running, open source log analysis tool for web servers and other services. It processes access logs to produce detailed usage statistics such as visitors, visits, pages, hits, search terms, host countries, browsers, operating systems, and error reports. The project is designed for administrators who want to understand traffic patterns from raw logs without relying on external analytics services. It can run from the command line or as a CGI script through a web server, and it supports multiple log formats, virtual hosts, plugins, DNS lookup, and several output styles including static HTML and dynamic CGI reports. The README also notes XML storage for analysis data, a Webmin module, and experimental PDF export. The project is deprecated, but the README preserves the original documentation and points users to Matomo Log Analytics as a successor.

Litlyx is an analytics platform aimed at website and web app owners who want a lightweight, cookie-free alternative to tools such as Google Analytics 4, PostHog, and Mixpanel. It provides a hosted cloud version as well as a self-hosted dashboard, making it suitable for teams that want either a managed service or control over their own deployment. The project works by adding a small script tag or installing the `litlyx-js` package, then initializing it with a workspace ID. Once connected, it tracks page visits, real-time users, unique visitors, and custom events, and it can also forward data to a self-hosted instance through configurable host, port, and security settings.

Prisme Analytics is an open source analytics service designed for websites and web applications. It focuses on privacy-preserving measurement, offering cookie-less tracking and anonymized data collection while still providing actionable reporting for product and marketing teams. The project is intended for self-hosters as well as users who prefer a managed option through Prisme Cloud. It relies on Grafana for the dashboard experience and emphasizes features such as custom events, campaign tracking, SPA compatibility, and automated filtering of bots, scrapers, and spam. The README also highlights user, team, permission, and organization management through Grafana integration, making it suitable for multi-user analytics setups.