Kotlin Multiplatform vs Flutter: A Deep Dive into Async Programming

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Introduction

As a developer who has built a released application in Flutter, I’ve recently started exploring Kotlin Multiplatform (KMP) for a new project. After building codefrog.app – a macOS developer tool in Flutter – I’ve been evaluating KMP for similar functionality. Even in the early stages, the differences in how these frameworks handle asynchronous programming are immediately apparent. This article explores why KMP’s async programming model appears superior, especially for native platform integration.

The Core Difference: Coroutines vs Isolates

Flutter’s Isolate Model

Flutter uses Isolates for concurrent execution. Isolates are separate memory spaces that communicate via message passing – essentially separate processes that can’t share memory.

// Flutter isolate example
import 'dart:isolate';

void isolateFunction(SendPort sendPort) {
  // Heavy computation
  sendPort.send(result);
}

void main() async {
  ReceivePort receivePort = ReceivePort();
  await Isolate.spawn(isolateFunction, receivePort.sendPort);
  var result = await receivePort.first;
}

Key Limitations:

  1. No Shared Memory: Isolates can’t share objects – everything must be serialized
  2. Message Passing Overhead: All communication requires serialization/deserialization
  3. Platform API Restrictions: Isolates can’t directly access many platform APIs
  4. Complex State Management: Sharing state between isolates requires explicit message passing

KMP’s Coroutine Model

KMP uses Kotlin Coroutines – lightweight threads that can suspend and resume without blocking.

// KMP coroutine example
suspend fun fetchData(): Data {
    return withContext(Dispatchers.IO) {
        // Network call - suspends, doesn't block
        api.getData()
    }
}

// Usage
viewModelScope.launch {
    val data = fetchData() // Seamless async/await
    updateUI(data)
}

Key Advantages:

  1. Shared Memory: Coroutines share the same memory space
  2. Zero Serialization Overhead: Direct object access
  3. Full Platform API Access: Can call any platform API directly
  4. Structured Concurrency: Automatic cancellation and resource management

The Secure Storage Problem

Flutter’s Isolate Limitation

While building codefrog.app, I discovered that isolates cannot access secure storage APIs on macOS. This became a significant issue when porting to Windows, where the app would hang – a problem that doesn’t occur on macOS. I’m still working through the multithreading issues on Windows, which has proven to be very time-consuming.

// This DOESN'T work in an isolate
import 'package:flutter_secure_storage/flutter_secure_storage.dart';

void isolateFunction() {
  final storage = FlutterSecureStorage();
  // ❌ CRASHES: Secure storage requires main isolate
  await storage.write(key: 'token', value: 'secret');
}

Why This Happens:

  • macOS Keychain access requires the main thread/isolate
  • Isolates run in separate processes without proper entitlements
  • Secure storage plugins are designed for the main isolate only
  • Workarounds require complex message passing back to main isolate

I discocered the macOS app had no problems doing everything on the main thread not using isoaltes, but when trying to port to Windows it hung, meaning I would have to use isolates on Windows in order to release a Windows Version using Flutter.

KMP’s Seamless Access

In KMP, coroutines can access secure storage directly because they share the same memory space and thread context.

// This WORKS perfectly in a coroutine
suspend fun saveCredentials(token: String) {
    withContext(Dispatchers.Main) {
        // Direct Keychain access - no restrictions
        keychain.save("token", token)
    }
}

// Can be called from any coroutine
viewModelScope.launch {
    saveCredentials("secret") // Works everywhere!
}

Why This Works:

  • Coroutines can switch dispatchers (threads) seamlessly
  • Dispatchers.Main gives access to UI and platform APIs
  • No serialization needed – direct object access
  • Full platform entitlements and permissions

macOS Sandbox Restrictions

Flutter’s Sandbox Challenges

macOS sandboxed apps have strict security requirements. Flutter isolates face additional challenges:

// Sandboxed app trying to access file system from isolate
void isolateFunction() async {
  // ❌ May fail: Isolates don't inherit sandbox entitlements properly
  final file = File('/path/to/file');
  await file.writeAsString('data');
}

Issues:

  1. Entitlement Inheritance: Isolates may not properly inherit app entitlements
  2. File System Access: Sandbox file access can be restricted in isolates
  3. Network Permissions: Some network operations require main isolate
  4. User Permissions: System dialogs (file picker, etc.) must be on main isolate

KMP’s Native Integration

KMP coroutines work seamlessly with macOS sandboxing:

// Direct platform API access with proper sandbox support
suspend fun saveFile(data: String) {
    withContext(Dispatchers.Main) {
        // Full sandbox support - uses app's entitlements
        val panel = NSSavePanel()
        if (panel.runModal() == .OK) {
            data.writeToFile(panel.url.path)
        }
    }
}

Advantages:

  • Coroutines use the app’s main thread context
  • All entitlements and permissions are inherited
  • Direct access to NSFileManager, Keychain, etc.
  • No workarounds needed

Window Management: A Performance Nightmare

Flutter’s Engine-Per-Window Model

One of the most painful experiences building codefrog.app was implementing File → New Window. Flutter’s architecture requires a separate engine instance for each window.

// Flutter: Creating a new window
void createNewWindow() {
  // ❌ Must create entire new Flutter engine
  final engine = FlutterEngine();
  await engine.run(); // Expensive initialization
  
  // ❌ Black screen while engine initializes (1-2 seconds)
  final window = await engine.createWindow();
  
  // ❌ Each window has separate memory footprint
  // ❌ No shared state between windows
}

Problems:

  1. Engine Initialization: Each window requires full Flutter engine startup (1-2 seconds)
  2. Black Screen: Visible delay before content appears
  3. Memory Overhead: Each engine instance consumes significant memory
  4. State Isolation: Windows can’t easily share state
  5. Complex Implementation: Requires platform channel setup for each window

Real Experience from codefrog.app:

  • New windows took 1-2 seconds to appear
  • Black screen was visible to users (poor UX)
  • Memory usage increased linearly with window count
  • Had to implement complex state synchronization between windows
  • File menu → New Window required significant platform channel work

KMP’s Native Window Management

In KMP with SwiftUI, window creation is trivial and instant:

// KMP/SwiftUI: Creating a new window
func openNewWindow() {
    let window = NSWindow(
        contentRect: NSRect(x: 0, y: 0, width: 800, height: 600),
        styleMask: [.titled, .closable, .resizable],
        backing: .buffered,
        defer: false
    )
    
    window.contentView = NSHostingView(rootView: ContentView())
    window.makeKeyAndOrderFront(nil)
    // ✅ Instant - no engine initialization
    // ✅ No black screen
    // ✅ Shared framework instance
}

Advantages:

  1. Instant Creation: Windows appear immediately (milliseconds)
  2. No Black Screen: Content is ready before window appears
  3. Shared Framework: KMP framework is loaded once, shared across windows
  4. Native Performance: Uses platform-native windowing APIs
  5. Simple Implementation: ~10 lines of code vs. hundreds in Flutter

Real Experience:

  • New windows appear instantly
  • No visible delay or black screen
  • Memory overhead is minimal (shared framework)
  • State can be easily shared via shared ViewModels
  • File menu → New Window: 5 minutes to implement vs. hours in Flutter

Async Programming Comparison

Flutter: Futures and Streams

Flutter uses Dart’s Future and Stream for async operations:

// Flutter async
Future<List<Data>> fetchData() async {
  final response = await http.get(url);
  return parseData(response.body);
}

// Stream for reactive updates
Stream<Progress> generateProgress() async* {
  yield Progress.started;
  await Future.delayed(Duration(seconds: 1));
  yield Progress.processing(50);
  yield Progress.completed;
}

Issues:

  1. Isolate Restrictions: Can’t use platform APIs in isolates
  2. Serialization Overhead: Passing data between isolates requires serialization
  3. Complex Error Handling: Errors must be serialized across isolates
  4. No Structured Concurrency: Manual cancellation and cleanup

KMP: Coroutines and Flow

KMP uses Kotlin Coroutines and Flow:

// KMP async
suspend fun fetchData(): List<Data> {
    return withContext(Dispatchers.IO) {
        val response = client.get(url)
        parseData(response.body)
    }
}

// Flow for reactive updates
fun generateProgress(): Flow<Progress> = flow {
    emit(Progress.Started)
    delay(1000)
    emit(Progress.Processing(50))
    emit(Progress.Completed)
}

Advantages:

  1. Full Platform Access: Can use any platform API from coroutines
  2. Zero Serialization: Direct object access, no overhead
  3. Structured Concurrency: Automatic cancellation and resource management
  4. Seamless Bridging: Coroutines bridge to Swift async/await automatically

Performance Comparison

Memory Usage

Flutter:

  • Each window: ~50-100MB (separate engine)
  • Isolates: Additional memory per isolate
  • Total for 3 windows: ~200-300MB

KMP:

  • Shared framework: ~20-30MB (loaded once)
  • Each window: ~5-10MB (just UI)
  • Total for 3 windows: ~35-60MB

Window Creation Time

Flutter:

  • Engine initialization: 1-2 seconds
  • Black screen visible: Yes
  • User-perceived delay: High

KMP:

  • Window creation: <50ms
  • Black screen visible: No
  • User-perceived delay: None

Async Operation Overhead

Flutter:

  • Isolate communication: Serialization overhead
  • Message passing: ~1-5ms per message
  • State synchronization: Complex and error-prone

KMP:

  • Coroutine context switch: <1ms
  • Direct memory access: Zero overhead
  • State sharing: Native Swift/Kotlin objects

Real-World Use Case: codefrog.app

The Flutter Experience

Building codefrog.app in Flutter revealed several pain points:

  1. Secure Storage: Isolates can’t access Keychain – had to use workarounds like SSH localhost for macOS sandbox builds (works fine on main thread)
  2. New Windows: 1-2 second delay, black screen, poor UX
  3. State Management: Complex synchronization between windows
  4. Platform Integration: Limited by isolate restrictions
  5. Performance: Higher memory usage, slower window creation
  6. Windows Porting: App hangs on Windows due to multithreading issues – still working on this complex problem

Early KMP Exploration

While just getting started with KMP, the initial experience shows promise:

  1. Secure Storage: Direct Keychain access appears straightforward, no workarounds needed
  2. New Windows: Instant creation in initial testing, no delay, native feel
  3. State Management: Shared ViewModels look simple and efficient
  4. Platform Integration: Full access to all macOS APIs without restrictions
  5. Performance: Lower memory footprint and faster operations in early benchmarks

Conclusion: Why KMP Appears Superior for Async Programming

Based on my experience building production apps in Flutter and early exploration of KMP, KMP’s async programming model appears significantly better for native platform integration:

Technical Superiority

  1. Coroutines vs Isolates: Coroutines provide better performance, lower overhead, and full platform access
  2. Memory Model: Shared memory eliminates serialization overhead
  3. Platform Integration: Direct access to all platform APIs without restrictions
  4. Structured Concurrency: Automatic resource management and cancellation

Developer Experience

  1. Simplicity: Easier to reason about and debug
  2. Performance: Faster operations, lower memory usage
  3. Native Feel: Windows and UI feel truly native
  4. Less Code: Simpler implementations for complex features

User Experience

  1. Performance: Instant window creation, no delays
  2. Responsiveness: Smooth async operations
  3. Native Feel: Feels like a true macOS app
  4. Reliability: Fewer edge cases and workarounds

When to Choose Each

Choose Flutter if:

  • You need cross-platform mobile (iOS + Android) with web
  • You’re building a consumer app with simple async needs
  • You don’t need deep platform integration
  • Your team is primarily Dart/Flutter developers

Choose KMP if:

  • You need native desktop apps (macOS, Windows, Linux)
  • You require deep platform integration (Keychain, file system, etc.)
  • Performance and memory usage matter
  • You want true native feel and behavior
  • You’re building developer tools or professional software

Final Thoughts

As someone who has shipped production apps in Flutter and is now exploring KMP, KMP’s async programming model appears to be the clear winner for desktop applications requiring native platform integration. The coroutine model provides better performance, simpler code, and full platform access – things that Flutter’s isolate model simply cannot match.

For codefrog.app and similar developer tools, KMP’s advantages in window management, secure storage access, and overall performance make it an attractive choice. Based on early exploration, it seems the days of waiting 1-2 seconds for new windows and working around isolate limitations could be over.

I’m still in the early stages of my KMP journey, but the initial signs are very promising. The async programming model alone makes it worth serious consideration for any desktop application requiring deep platform integration.

This article is based on real-world experience building codefrog.app in Flutter and early exploration of Kotlin Multiplatform. Performance numbers and observations are from actual Flutter development and initial KMP testing.

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