Data Persistence

English topic guide inspired by the original iOS Developer Notebook, expanded for both iOS and Android teams.

What this topic covers

Core mental models and architecture decisions
Implementation patterns for production apps
Common pitfalls and how to avoid them
Release and QA checklist

Execution checklist

Define one measurable outcome before coding.
Build a minimal feature slice in one screen/flow.
Add unit tests and one integration/UI test.
Validate on small + large devices.

iOS implementation notes

Use native platform APIs first and wrap in thin service layers.
Keep business logic out of views/view controllers.
Adopt structured concurrency and explicit error handling.
Instrument performance and crash metrics before release.

Android implementation notes

Use clear layer boundaries (UI, domain, data).
Prefer immutable UI state and unidirectional data flow.
Handle network/cache failures with explicit fallback states.
Profile startup and rendering performance on mid-range devices.

Code examples

Swift

@Model final class TaskItem {
  var title: String
  var done: Bool
  init(title: String, done: Bool = false) { self.title = title; self.done = done }
}

Kotlin

@Entity data class TaskEntity(@PrimaryKey val id: String, val title: String, val done: Boolean)
@Dao interface TaskDao { @Query("SELECT * FROM TaskEntity") suspend fun all(): List }

What this topic covers

Execution checklist

iOS implementation notes

Android implementation notes

Code examples

Swift

Kotlin

Reference links

Related topics