This project is a simplified system design implementation of a file storage and synchronization system inspired by Dropbox. It focuses on how files are stored, versioned, and synchronized across multiple clients in a distributed environment.
The goal is to understand how reliable file sync systems are built, including versioning, conflict handling, and efficient data transfer.
File synchronization systems must keep files consistent across multiple devices while handling concurrent edits, network interruptions, and partial uploads. These systems must efficiently detect changes, transfer only what is needed, and ensure data integrity across distributed clients.
This project explores how to design a simplified file storage and sync system that supports upload, download, and multi-device synchronization.
- Understand file synchronization systems
- Learn how change detection works (hashing / diffing concepts)
- Explore versioning and conflict resolution strategies
- Understand chunk-based file transfer concepts
- Learn consistency challenges in distributed storage systems
- Explore tradeoffs between storage efficiency and simplicity
- Build intuition for client-server sync architectures
- Upload files from client to server
- Download files from storage system
- Store file metadata and versions
- Sync files across multiple devices
- Detect file changes (hash-based or timestamp-based)
- Resolve conflicts (last-write-wins or versioning conceptually)
- Maintain file history
- Restore previous versions (conceptual or implemented)
- Track file updates over time
- Chunked uploads/downloads (conceptual)
- Delta sync (only changed parts)
- Reduce redundant data transfer
- Watches local file system for changes
- Uploads updates to server
- Downloads remote changes
- Coordinates file versions across clients
- Detects conflicts and resolves versions
- Maintains metadata about files
- Stores file blobs
- Maintains version history
- Ensures durability and integrity
- Tracks file ownership and versions
- Maps files to storage locations
- Supports fast lookup for sync operations
- Conflict resolution in concurrent edits
- Efficient change detection mechanisms
- Network reliability and partial uploads
- Tradeoffs between storage cost and version history
- Consistency across multiple devices
- Scaling metadata-heavy systems
- Handling large file transfers efficiently
- Distributed Systems (coordination and consistency challenges)
- Message Queue (sync event propagation)
- Caching system (frequent file metadata access)
- Load Testing (sync performance under concurrency)
- Backend services (file APIs and storage layer)
🟡 Planned