Spike is an open-source, self-hosted alternative to tools like Fathom Analytics, Plausible Analytics, and Matomo, focusing on privacy-respecting web analytics. It's designed to be lightweight, fast, and easy to understand, both for users and developers. Unlike many analytics platforms, Spike prioritizes simplicity and avoids complex data collection and processing, aiming to provide essential website statistics without compromising user privacy or requiring extensive server resources. The core philosophy revolves around providing *just enough* data to be useful, without the bloat of feature-rich, but potentially intrusive, alternatives.

The repository contains the source code for both the Spike server (written in Go) and the Spike client (a JavaScript snippet for website integration). The server handles data collection, processing, and storage, while the client tracks page views and other basic events on the user's website. A key architectural decision is the use of SQLite as the database, making setup and maintenance incredibly straightforward – no need for complex database servers like PostgreSQL or MySQL. This simplicity extends to the deployment process; Spike is designed to be easily deployable using Docker, further lowering the barrier to entry for self-hosting. The project is actively maintained and welcomes contributions from the community.

Data collection in Spike is minimal. It primarily tracks page views, referrers, user agents (though these can be anonymized), and basic geographical information derived from IP addresses (which can also be disabled). Crucially, Spike *does not* use cookies or track any personally identifiable information (PII). This commitment to privacy is a central tenet of the project. The collected data is aggregated and presented through a clean, intuitive web interface built with React. The dashboard provides key metrics like total page views, unique visitors, referring websites, and geographical distribution of visitors. It also offers basic filtering options to analyze data over specific time periods.

The repository is well-structured and documented, making it relatively easy to understand the codebase and contribute to the project. The `cmd/spike` directory contains the main server application, while `web/` houses the React-based frontend. The `pkg/` directory contains reusable Go packages. The documentation covers installation, configuration, deployment, and usage. The project utilizes standard Go tooling for building and testing. Furthermore, the repository includes a Dockerfile for containerized deployment, simplifying the process of running Spike in various environments.

In essence, Spike offers a compelling solution for website owners who value privacy and simplicity in their analytics. It provides essential website statistics without the complexity and privacy concerns associated with larger, more feature-rich platforms. Its lightweight nature, ease of deployment, and commitment to privacy make it an attractive option for individuals and small businesses looking for a self-hosted analytics solution. The active development and welcoming community suggest that Spike will continue to evolve and improve as a viable alternative in the web analytics landscape.