Offline-First Apps: Caching Strategies with Hive and Drift in Flutter

Introduction

Offline-first mobile development ensures that your Flutter app remains responsive and functional even when network connectivity is intermittent or unavailable. By caching data locally and synchronizing with a remote API when possible, you create a seamless user experience. In this tutorial, we’ll explore two popular Flutter solutions—Hive and Drift—and discuss strategies for caching, syncing, and conflict resolution.

Hive for lightweight local caching

Hive is a fast, key-value database written in pure Dart. It’s ideal for storing small objects, user settings, or simple lists. Because it doesn’t require an external engine, Hive excels in scenarios where read/write performance matters and relational queries are minimal.

To get started, add the dependency in pubspec.yaml:

dependencies:
  hive: ^2.0.0
  hive_flutter

Initialize Hive in main():

await Hive.initFlutter();
var box = await Hive.openBox('cacheBox');
box.put('lastFetch', DateTime.now().toIso8601String());
var cached = box.get('userProfile');

Drift for structured relational storage

Drift (formerly Moor) brings SQLite support to Flutter with a type-safe, reactive API. It’s ideal for complex data models, joins, and migrations. Define tables and DAOs to manage entities and queries over time.

Add dependencies:

dependencies:
  drift: ^2.0.0
  drift_flutter: ^2.0.0
  sqlite3_flutter_libs

Define a table and database:

class Notes extends Table {
  IntColumn get id => integer().autoIncrement()();
  TextColumn get content => text()();
  DateTimeColumn get modifiedAt => dateTime()();
}

@DriftDatabase(tables: [Notes])
class AppDatabase extends _$AppDatabase {
  AppDatabase() : super(_openConnection());
}

Data synchronization patterns

An offline-first strategy requires reliable sync between local caches and a server. Two common patterns:

Push-based sync: Record local changes in a queue and push them to the server on connectivity. Mark each record as synced. Use exponential backoff for retries.

Pull-based sync: Fetch deltas from the server by timestamp or version. Merge remote updates into local storage. Perform this in background isolates to avoid blocking the UI.

Combine both: On app launch or resume, first push local changes, then pull server updates to keep both sides consistent.

Conflict resolution strategies

Conflicts occur when the same record is modified locally and remotely before sync. Choose a strategy based on your business logic:

• Last write wins: Compare timestamps and accept the most recent change.

• Merge fields: For non-overlapping fields, merge local and server changes.

• User intervention: Mark conflicts and prompt the user to resolve.

Implement conflict resolution in your sync layer. For Drift, wrap updates in transactions. For Hive, filter through conflict handlers before committing to the box.

Combining Hive and Drift in a hybrid cache

For optimal performance, combine the strengths of both stores:

• Hive for ephemeral or lightweight caches such as API responses, feature flags, or recent activity lists.

• Drift for core business data requiring relational integrity, complex queries, and migrations.

Workflow:

1. On API response, cache raw JSON in Hive for quick access.

2. Parse and normalize critical entities into Drift tables for robust storage.

3. Use Drift streams to drive UI updates while Hive serves as a fast lookup layer.

This hybrid approach reduces startup lag, minimizes database overhead for trivial data, and retains powerful query capabilities where needed.

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Conclusion

Offline-first Flutter apps deliver robust performance and reliability by caching locally and synchronizing intelligently. Hive offers blazing-fast key-value storage, while Drift provides a full SQLite-backed relational database with reactive queries. By employing push/pull sync patterns and clear conflict resolution strategies—alongside a hybrid cache architecture—you create a seamless user experience across network conditions.