Offline-First Architecture

Offline-first architecture treats local storage as the primary data source. Network connectivity is used for synchronization rather than as a requirement for application functionality.

Core Principles

Principle	Description
Local-first	Write operations target local storage first, then synchronize to remote servers
Optimistic UI	The interface reflects changes immediately without waiting for server confirmation
Conflict resolution	The system handles data conflicts when multiple sources modify the same data
Background sync	Synchronization occurs automatically when connectivity is restored

Architecture Pattern

UI <-> Local Database <-> Sync Engine <-> Remote Server
              |
        Pending Queue

Local Storage Options

Platform	Storage Options
iOS	Core Data, Realm, SQLite, UserDefaults
Android	Room, Realm, SQLite, SharedPreferences
Cross-platform	SQLite, Realm, Hive

Sync Strategies

Optimistic Updates

Implementation approach:

1. Create the item locally with a pending status and save to the local database
2. Update the UI immediately to reflect the new item
3. Queue the creation operation for synchronization when connectivity is available

This pattern provides instant feedback to users while ensuring data is eventually synchronized with the server.

Conflict Resolution Strategies

Strategy	Description	Trade-offs
Last-write-wins	The most recent write overwrites previous values	Simple to implement; may lose data
Merge	Combines changes when fields do not conflict	Preserves more data; complex to implement
User resolution	Presents conflicts to the user for manual resolution	Highest data accuracy; requires user action

Network Monitoring

Implementation approach: Create a network monitor class that observes connectivity changes. On iOS, use NWPathMonitor to receive callbacks when network status changes. On Android, use ConnectivityManager with a NetworkCallback. When connectivity is restored, trigger the sync engine to process the pending queue of operations.

Design Considerations

Consideration	Description
Data freshness	The acceptable age of cached data varies by application type. Messaging applications require near-real-time data; news readers tolerate older content.
Storage limits	Mobile devices have finite storage. Implement eviction policies for cached data.
Conflict frequency	Multi-device editing of the same data increases conflict likelihood.
Partial sync	Selective synchronization reduces bandwidth and storage requirements compared to full synchronization.