I developed an open-source task management software based on CRDT with a local-first approach. The motivation was that I primarily manage personal tasks without needing collaboration features, and tools like Linear are overly complex for my use case.

This architecture offers several advantages:

1. Data is stored locally, resulting in extremely fast software response times 2. Supports convenient full database export and import 3. Server-side logic is lightweight, requiring minimal performance overhead and development complexity, with all business logic implemented on the client 4. Simplified feature development, requiring only local logic operations

There are also some limitations:

1. Only suitable for text data storage; object storage services are recommended for images and large files 2. Synchronization-related code requires extra caution in development, as bugs could have serious consequences 3. Implementing collaborative features with end-to-end encryption is relatively complex

The technical architecture is designed as follows:

1. Built on the Loro CRDT open-source library, allowing me to focus on business logic development

2. Data processing flow: User operations trigger CRDT model updates, which export JSON state to update the UI. Simultaneously, data is written to the local database and synchronized with the server.

3. The local storage layer is abstracted through three unified interfaces (list, save, read), using platform-appropriate storage solutions: IndexedDB for browsers, file system for Electron desktop, and Capacitor Filesystem for iOS and Android.

4. Implemented end-to-end encryption and incremental synchronization. Before syncing, the system calculates differences based on server and client versions, encrypts data using AES before uploading. The server maintains a base version with its content and incremental patches between versions. When accumulated patches reach a certain size, the system uploads an encrypted full database as the new base version, keeping subsequent patches lightweight.

If you're interested in this project, please visit https://github.com/hamsterbase/tasks