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.

PostHog is an open source platform for product teams that want to understand user behavior, diagnose issues, and ship improvements from one place. The README presents it as a tool for building “self-driving” products by turning signals such as errors, rage clicks, failed queries, and other product data into actionable reports and fixes. It combines analytics, replay, experimentation, feature management, observability, surveys, data warehousing, and pipelines into a single system. The project is aimed at teams that want to instrument web, mobile, and backend applications, with integrations through a JavaScript snippet, SDKs, an API, Slack, desktop tooling, and an MCP connection. The README also emphasizes a hosted cloud offering, while still documenting a self-hosted hobby deployment path for Linux with Docker.

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.

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.

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 standard analytics reporting without cookies, while also offering more advanced product analytics workflows such as session replay, funnels, journeys, retention, and custom events. The project supports hosted use as well as self-hosting on a VPS, and its documentation points users to setup, configuration, and usage guidance. The README highlights support for organizations and unlimited sites, suggesting it is intended for multi-site analytics deployments and collaborative use rather than a single-person tool. It also includes screenshots of dashboards for maps, replay, funnels, goals, users, errors, retention, and web vitals.

Evidence is an open-source business intelligence tool aimed at teams that want to build data products with a code-based workflow instead of drag-and-drop BI. It turns markdown files with embedded SQL into a website, letting users define queries, render charts and components from query results, and create reusable templates for generating many pages. The project is positioned for developers and data practitioners who prefer working in code and want to publish reports as static sites. The README points users to a VSCode extension for creating projects and notes that deployments can be self-hosted on platforms like Netlify, Vercel, or other static hosting infrastructure.

Countly is a privacy-focused analytics and customer engagement platform designed for organizations that want control over their data and deployment. The project emphasizes self-hosting, with deployment options for on-premises infrastructure or private cloud environments, and it is presented as suitable for teams that need flexibility, compliance, and long-term autonomy. The server repository provides the backend for Countly’s analytics product, including data collection, reporting, notifications, remote configuration, and user/application management. It exposes read and write APIs and is built around a plugin architecture, allowing teams to extend existing capabilities or add new ones. The README also positions the project as supporting multiple application types and use cases, from mobile and web analytics to crash reporting and customer engagement workflows.

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.

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.