| name | axiom-core-data-diag |
| description | Use when debugging schema migration crashes, concurrency thread-confinement errors, N+1 query performance, SwiftData to Core Data bridging, or testing migrations without data loss - systematic Core Data diagnostics with safety-first migration patterns |
| license | MIT |
| metadata | {"version":"1.0.0"} |
Core Data Diagnostics & Migration
Overview
Core Data issues manifest as production crashes from schema mismatches, mysterious concurrency errors, performance degradation under load, and data corruption from unsafe migrations. Core principle 85% of Core Data problems stem from misunderstanding thread-confinement, schema migration requirements, and relationship query patterns—not Core Data defects.
Red Flags — Suspect Core Data Issue
If you see ANY of these, suspect a Core Data misunderstanding, not framework breakage:
- Crash on production launch: "Unresolvable fault" after schema change
- Thread-confinement error: "Accessing NSManagedObject on a different thread"
- App suddenly slow after adding a User→Posts relationship
- SwiftData app needs complex features; considering mixing Core Data alongside
- Schema migration works in simulator but crashes on production
- ❌ FORBIDDEN "Core Data is broken, we need a different database"
- Core Data handles trillions of records in production apps
- Schema mismatches and thread errors are always developer code, not framework
- Do not rationalize away the issue—diagnose it
Critical distinction Simulator deletes the database on each rebuild, hiding schema mismatch issues. Real devices keep persistent databases and crash immediately on schema mismatch. MANDATORY: Test migrations on real device with real data before shipping.
Mandatory First Steps
ALWAYS run these FIRST (before changing code):
let coordinator = persistentStoreCoordinator
let model = coordinator.managedObjectModel
let store = coordinator.persistentStores.first
do {
let metadata = try NSPersistentStoreCoordinator.metadataForPersistentStore(
ofType: NSSQLiteStoreType,
at: storeURL,
options: nil
)
print("Store version identifier: \(metadata[NSStoreModelVersionIdentifiersKey] ?? "unknown")")
print("App model version: \(model.versionIdentifiers)")
} catch {
print("Schema check error: \(error)")
}
print("Main thread? \(Thread.isMainThread)")
print("Context concurrency type: \(context.concurrencyType.rawValue)")
print("Accessing from: \(Thread.current)")
if #available(iOS 17.0, *) {
print("Using both SwiftData and Core Data on same store?")
}
What this tells you
- Schema mismatch → Proceed to Pattern 1 (lightweight migration decision)
- Thread-confinement error → Proceed to Pattern 2 (async/await concurrency)
- N+1 queries → Proceed to Pattern 3 (relationship prefetching)
- SwiftData + Core Data conflict → Proceed to Pattern 4 (bridging)
- Slow after migration → Proceed to Pattern 5 (testing safety)
MANDATORY INTERPRETATION
Before changing ANY code, identify ONE of these:
- If crash is "Unresolvable fault" AND store/model versions differ → Schema mismatch (not user error)
- If crash mentions "different thread" AND you're using DispatchQueue → Thread-confinement (not thread-safe design)
- If performance degrades with relationship access → N+1 queries (check SQL log)
- If SwiftData and Core Data code exist together → Conflicting data layers (architectural issue)
- If migration test passes but production fails → Edge case in real data (testing gap)
If diagnostics are contradictory or unclear
- STOP. Do NOT proceed to patterns yet
- Add print statements to every NSManagedObject access (thread check)
- Add
-com.apple.CoreData.SQLDebug 1 and count SQL queries
- Establish baseline: what's actually happening vs. what you assumed
Decision Tree
Core Data problem suspected?
├─ Crash: "Unresolvable fault"?
│ └─ YES → Schema mismatch (store ≠ app model)
│ ├─ Add new required field? → Pattern 1a (lightweight migration)
│ ├─ Remove field, rename, or change type? → Pattern 1b (heavy migration)
│ └─ Don't know how to fix? → Pattern 1c (testing safety)
│
├─ Crash: "different thread"?
│ └─ YES → Thread-confinement violated
│ ├─ Using DispatchQueue for background work? → Pattern 2a (async context)
│ ├─ Mixing Core Data with async/await? → Pattern 2b (structured concurrency)
│ └─ SwiftUI @FetchRequest causing issues? → Pattern 2c (@FetchRequest safety)
│
├─ Performance: App became slow?
│ └─ YES → Likely N+1 queries
│ ├─ Accessing user.posts in loop? → Pattern 3a (prefetching)
│ ├─ Large result set? → Pattern 3b (batch sizing)
│ └─ Just added relationships? → Pattern 3c (relationship tuning)
│
├─ Using both SwiftData and Core Data?
│ └─ YES → Data layer conflict
│ ├─ Need Core Data features SwiftData lacks? → Pattern 4a (drop to Core Data)
│ ├─ Already committed to SwiftData? → Pattern 4b (stay in SwiftData)
│ └─ Unsure which to use? → Pattern 4c (decision framework)
│
└─ Migration works locally but crashes in production?
└─ YES → Testing gap
├─ Didn't test with real data? → Pattern 5a (production testing)
├─ Schema change affects large dataset? → Pattern 5b (migration safety)
└─ Need verification before shipping? → Pattern 5c (pre-deployment checklist)
Common Patterns
Pattern Selection Rules (MANDATORY)
Apply ONE pattern at a time, starting with diagnostics
- Always start with Mandatory First Steps — Identify the actual problem
- Run decision tree — Narrow to specific pattern
- Apply ONE pattern — Don't combine patterns
- Test on real device — Simulator hides issues
- Verify with migration test — Before deploying
FORBIDDEN
- ❌ Changing code without diagnostics
- ❌ Skipping real device testing
- ❌ Using simulator success as proof of migration safety
- ❌ Mixing multiple migration patterns
- ❌ Deploying migrations without pre-deployment verification
Pattern 1a: Lightweight Migration (Simple Schema Changes)
PRINCIPLE Core Data can automatically migrate simple schemas (additive changes) without data loss if done correctly.
✅ SAFE Lightweight Migrations
- Adding new optional field:
@NSManaged var nickname: String?
- Adding new required field WITH default: Create attribute with default value
- Renaming entity or attribute: Use mapping model with automatic mapping
- Removing unused field: Just delete from model (data stays on disk, ignored)
❌ WRONG (Crashes production)
@NSManaged var userID: String
@NSManaged var createdAt: Date
✅ CORRECT (Safe lightweight migration)
@NSManaged var userID: String = UUID().uuidString
When this works
- Adding optional fields (always safe)
- Adding required fields WITH default values
- Removing fields
- Renaming entities/attributes with mapping model
When this FAILS (don't try lightweight)
- Changing field type (String → Int)
- Making optional field required (data has nulls, can't convert)
- Complex relationship changes
- Custom data transformations needed
Time cost 5-10 minutes for lightweight migration setup
Pattern 1b: Heavy Migration (Complex Schema Changes)
PRINCIPLE When lightweight migration won't work, use NSEntityMigrationPolicy for custom transformation logic.
Use when
- Changing field types (String → Date)
- Making optional required (need to populate existing nulls)
- Complex relationship restructuring
- Custom data transformations (e.g., split "firstName lastName" into separate fields)
Example: Convert String dates to Date objects
class DateMigrationPolicy: NSEntityMigrationPolicy {
override func createDestinationInstances(
forSource sInstance: NSManagedObject,
in mapping: NSEntityMapping,
manager: NSMigrationManager
) throws {
let destination = NSEntityDescription.insertNewObject(
forEntityName: mapping.destinationEntityName ?? "",
into: manager.destinationContext
)
for key in sInstance.entity.attributesByName.keys {
destination.setValue(sInstance.value(forKey: key), forKey: key)
}
if let dateString = sInstance.value(forKey: "createdAt") as? String,
let date = ISO8601DateFormatter().date(from: dateString) {
destination.setValue(date, forKey: "createdAt")
} else {
destination.setValue(Date(), forKey: "createdAt")
}
manager.associate(source: sInstance, withDestinationInstance: destination, for: mapping)
}
}
Critical safety rules
- ALWAYS backup database before testing migration
- Test migration on COPY of production data
- Verify data integrity after migration (spot checks)
- Create rollback plan if migration fails
Time cost 30-60 minutes per migration + testing
Pattern 2a: Async Context for Background Fetching
PRINCIPLE Core Data objects are thread-confined. Fetch on background thread, convert to lightweight representations for main thread.
❌ WRONG (Thread-confinement crash)
DispatchQueue.global().async {
let context = NSManagedObjectContext(concurrencyType: .mainQueueConcurrencyType)
let results = try! context.fetch(request)
DispatchQueue.main.async {
self.objects = results
}
}
✅ CORRECT (Use private queue context for background work)
let backgroundContext = NSManagedObjectContext(concurrencyType: .privateQueueConcurrencyType)
backgroundContext.parent = viewContext
backgroundContext.perform {
do {
let results = try backgroundContext.fetch(userRequest)
let userIDs = results.map { $0.id }
DispatchQueue.main.async {
let mainResults = try self.viewContext.fetch(request)
self.objects = mainResults
}
} catch {
print("Fetch error: \(error)")
}
}
Why this works
- Background context fetches on background thread (safe)
- Converts heavy objects to lightweight values (safe to pass to main)
- Main context fetches on main thread (safe)
- No thread-confined objects crossing thread boundaries
Time cost 10 minutes to restructure
Pattern 2b: Structured Concurrency (async/await with Core Data)
PRINCIPLE Use NSPersistentContainer or NSManagedObjectContext async methods for Swift Concurrency compatibility.
✅ CORRECT (iOS 13+ async APIs)
let users = try await viewContext.perform {
try viewContext.fetch(userRequest)
}
let users = try await container.mainContext.fetch(userRequest)
let backgroundUsers = try await backgroundContext.perform {
try backgroundContext.fetch(userRequest)
}
❌ WRONG (Mixing Swift Concurrency with DispatchQueue)
async {
DispatchQueue.global().async {
try context.fetch(request)
}
}
Time cost 5 minutes to convert from DispatchQueue to async/await
Pattern 3a: Relationship Prefetching (Prevent N+1)
PRINCIPLE Tell Core Data to fetch relationships eagerly instead of lazy-loading on access.
❌ WRONG (N+1 query pattern)
let users = try context.fetch(userRequest)
for user in users {
let posts = user.posts
}
✅ CORRECT (Prefetch relationships)
var request = NSFetchRequest<User>(entityName: "User")
request.relationshipKeyPathsForPrefetching = ["posts", "comments"]
let users = try context.fetch(request)
for user in users {
let posts = user.posts
}
Other optimization patterns
request.fetchBatchSize = 100
request.returnsObjectsAsFaults = false
request.returnsDistinctResults = true
Time cost 2-5 minutes to add prefetching
Pattern 3b: Fetch Batch Sizing
PRINCIPLE For large result sets, fetch in batches to manage memory.
Example: Scrolling through 100,000 users
var request = NSFetchRequest<User>(entityName: "User")
request.fetchBatchSize = 100
request.sortDescriptors = [NSSortDescriptor(key: "id", ascending: true)]
let results = try context.fetch(request)
for user in results {
}
Time cost 3 minutes to tune batch size
Pattern 4a: Core Data Features SwiftData Doesn't Have
Scenario You chose SwiftData, but need features it lacks.
SwiftData lacks
- Complex migrations (auto-migration only)
- Custom validation (before save)
- Relationship delete rules (cascade, deny, nullify)
- Direct SQL queries
- Advanced prefetching
- Faulting control
When to drop to Core Data from SwiftData
- Need custom migrations
- Need validation logic
- Need complex relationship rules
- Need raw SQL for performance
- Need fault tolerance patterns
✅ CORRECT (Hybrid approach when necessary)
@Model final class Note {
var id: String
var title: String
}
let backgroundContext = NSManagedObjectContext(concurrencyType: .privateQueueConcurrencyType)
backgroundContext.parent = container.viewContext
let results = try backgroundContext.perform {
try backgroundContext.fetch(coreDataRequest)
}
CRITICAL Do NOT access the same entity from both SwiftData and Core Data simultaneously. One or the other, not both.
Time cost 30-60 minutes to create bridging layer
Pattern 4b: Stay in SwiftData (Recommended for New Projects)
Scenario You're in SwiftData and wondering if you need Core Data.
SwiftData provides 80% of Core Data functionality for modern apps
- Type-safe models (@Model)
- Reactive queries (@Query)
- CloudKit sync (built-in)
- Automatic migrations (for simple changes)
- Proper async/await integration
When SwiftData is sufficient
- Simple schemas (users, notes, todos)
- Minimal relationship complexity
- CloudKit sync needed
- iOS 17+ requirement acceptable
- No legacy Core Data code to maintain
Decision: Stay in SwiftData if you can answer YES to 3+ of these
- ✅ iOS 17+ only (no iOS 16 support needed)
- ✅ Simple relationships (1-to-many, not many-to-many)
- ✅ Standard migrations (add fields, remove fields)
- ✅ CloudKit sync beneficial
- ✅ Type safety important
Decision: Drop to Core Data if
- ❌ Need iOS 16 support (SwiftData iOS 17+ only)
- ❌ Complex relationship rules (cascade rules, constraints)
- ❌ Custom migrations required
- ❌ Raw SQL needed for performance
- ❌ Already have Core Data codebase
Time cost 0 minutes (decision only)
Pattern 5a: Safe Production Testing Before Migration
PRINCIPLE Never deploy a migration without testing against real data.
MANDATORY Pre-Deployment Checklist
@Test func testProductionDataMigration() throws {
let testDB = tempDirectory.appendingPathComponent("test.sqlite")
try FileManager.default.copyItem(from: prodDatabase, to: testDB)
var config = ModelConfiguration(url: testDB, isStoredInMemory: false)
let container = try ModelContainer(for: User.self, configurations: [config])
let context = container.mainContext
let allUsers = try context.fetch(FetchDescriptor<User>())
guard let user1 = allUsers.first(where: { $0.id == "test-id-1" }) else {
throw MigrationError.missingUser
}
XCTAssertEqual(user1.name, "Expected Name")
XCTAssertNotNil(user1.createdAt)
XCTAssertEqual(user1.posts.count, expectedPostCount)
}
Safety rules
- ❌ NEVER test migrations with simulator (simulator deletes DB)
- ✅ ALWAYS test with copy of real production data
- ✅ ALWAYS verify spot checks (specific records)
- ✅ ALWAYS check relationships loaded correctly
- ✅ ALWAYS have rollback plan documented
Time cost 15-30 minutes to create migration test
Pattern 5c: Pre-Deployment Verification Checklist
MANDATORY before shipping ANY Core Data change
If you answer NO to any item
- ❌ DO NOT SHIP
- Go back, fix the issue, re-test
- One "NO" = data loss risk
Time cost 5 minutes checklist
Quick Reference Table
| Issue | Check | Fix |
|---|
| "Unresolvable fault" crash | Do store/model versions match? | Create .xcdatamodel version + mapping model |
| "Different thread" crash | Is fetch happening on main thread? | Use private queue context for background work |
| App became slow | Are relationships being prefetched? | Add relationshipKeyPathsForPrefetching |
| N+1 query performance | Check -com.apple.CoreData.SQLDebug 1 logs | Add prefetching or convert to lightweight representation |
| SwiftData needs Core Data features | Do you need custom migrations? | Use Core Data NSEntityMigrationPolicy |
| Not sure about SwiftData vs. Core Data | Do you need iOS 16 support? | Use Core Data for iOS 16, SwiftData for iOS 17+ |
| Migration test works, production fails | Did you test with real data? | Create migration test with production database copy |
When You're Stuck After 30 Minutes
If you've spent >30 minutes and the Core Data issue persists:
STOP. You either
- Skipped mandatory diagnostics (most common)
- Misidentified the actual problem
- Applied wrong pattern for your symptom
- Haven't tested on real device/real data
- Have edge case requiring custom NSEntityMigrationPolicy
MANDATORY checklist before claiming "skill didn't work"
If ALL boxes are checked and still broken
- You need custom NSEntityMigrationPolicy (not covered by basic patterns)
- Time cost: 60-90 minutes for complex migration
- Ask: "What data transformation is actually needed?" and implement custom policy
Time cost transparency
- Pattern 1 (lightweight migration): 5-10 minutes
- Pattern 1 (heavy migration with custom policy): 60-90 minutes
- Pattern 2 (concurrency): 5-10 minutes
- Pattern 3 (prefetching): 2-5 minutes
- Pattern 4 (bridging): 30-60 minutes
- Pattern 5 (testing): 15-30 minutes
Common Mistakes
❌ Testing migration in simulator only
- Simulator deletes database on rebuild, hiding schema mismatches
- Fix: ALWAYS test on real device or with production database copy
❌ Assuming default values protect against data loss
- Default values only work for new records, not existing data
- Fix: Use NSEntityMigrationPolicy for existing data
❌ Accessing Core Data objects across threads without conversion
- Objects are thread-confined, can't cross thread boundaries
- Fix: Convert to lightweight representations before passing to other threads
❌ Not realizing relationship access = database query
user.posts triggers a fetch for EACH user (N+1)
- Fix: Use relationshipKeyPathsForPrefetching or extract IDs first
❌ Mixing SwiftData and Core Data on same store
- Both layers can't access the same database simultaneously
- Fix: Choose one layer, or use hybrid approach with separate entities
❌ Deploying migrations without pre-deployment testing
- Edge cases in production data cause crashes
- Fix: MANDATORY migration test with real production data
❌ Rationalizing: "I'll just delete the data"
- ❌ FORBIDDEN: Users won't appreciate losing their data
- Users uninstall and leave bad reviews
- Fix: Invest in safe migration testing
Production Crisis Pressure: Defending Safe Migration Patterns
The Problem
Under production crisis pressure, you'll face requests to:
- "Users are crashing - just delete the database and start fresh"
- "Migration is taking too long - skip the testing and ship it"
- "We can't wait 2 days for proper migration - hack it together"
- "Schema mismatch? Just force-create a new store"
These sound like pragmatic crisis responses. But they cause data loss and permanent user trust damage. Your job: defend using data safety principles and customer impact, not fear of pressure.
Red Flags — PM/Manager Requests That Cause Data Loss
If you hear ANY of these during a production crisis, STOP and reference this skill:
- ❌ "Delete the persistent store and start fresh" – Users lose ALL their data permanently
- ❌ "Force lightweight migration without testing" – High risk of data corruption in production
- ❌ "Skip migration and create new store" – Abandons existing user data
- ❌ "We'll fix data issues after launch" – Impossible to recover lost/corrupted data
- ❌ "Just ship it, we can handle support tickets" – Data loss creates permanent user churn
- ❌ "Test on simulator is enough" – Simulator deletes database on rebuild, hides schema mismatches
How to Push Back Professionally
Step 1: Quantify the Customer Impact
"I want to resolve this crash ASAP, but let me show you what deleting the store means:
Current situation:
- 10,000 active users with data
- Average 50 items per user (500,000 total records)
- Users have 1 week to 2 years of accumulated data
If we delete the store:
- 10,000 users lose ALL their data on next app launch
- Uninstall rate: 60-80% (industry standard after data loss)
- App Store reviews: Expect 1-star reviews citing data loss
- Recovery: Impossible - data is gone permanently
Safe alternative:
- Test migration on real device with production data copy (2-4 hours)
- Deploy migration that preserves user data
- Uninstall rate: <5% (standard update churn)"
Step 2: Demonstrate the Risk
Show the PM/manager what happens:
- Copy production database from device backup
- Run proposed "quick fix" (delete store)
- Show: All user data gone permanently
- Show alternative: Safe migration preserving data
- Time comparison: 30 min hack vs. 2-4 hour safe migration
Reference
- "Users don't forgive data loss" (App Store review patterns)
- Migration testing on real device prevents 95% of production crashes
- Schema mismatch crashes affect 100% of existing users
Step 3: Offer Compromise
"I can get us through this crisis while protecting user data:
#### Fast track (4 hours total)
1. Copy production database from TestFlight user (30 min)
2. Write and test migration on real device copy (2 hours)
3. Submit build with tested migration (30 min)
4. Monitor first 100 updates for crashes (1 hour)
#### Fallback if migration fails
- Have "delete store" build ready as Plan B
- Only deploy if migration shows 100% failure rate
- Communicate data loss to users proactively
This approach:
- Tries safe path first (protects user data)
- Has emergency fallback (if migration impossible)
- Honest timeline (4 hours vs. "just delete it" 30 min)"
Step 4: Document the Decision
If overruled (PM insists on deleting store):
Slack message to PM + team:
"Production crisis: Schema mismatch causing crashes for existing users.
PM decision: Delete persistent store to resolve immediately.
Impact assessment:
- 10,000 users lose ALL data permanently on next app launch
- Expected uninstall rate: 60-80% based on data loss patterns
- App Store review damage: High risk of 1-star reviews
- Customer support: Expect high volume of data loss complaints
- Recovery: Impossible - deleted data cannot be recovered
Alternative proposed (4-hour safe migration) was declined due to urgency.
I'm flagging this decision proactively so we can:
1. Prepare support team for data loss complaints
2. Draft App Store response to expected negative reviews
3. Consider user communication about data loss before launch"
Why this works
- You're not questioning their judgment under pressure
- You're quantifying user impact (business consequences)
- You're offering a solution with honest timeline
- You're providing fallback option (not blocking progress)
- You're documenting the decision (protects you post-launch)
Real-World Example: Production Crash (500K Active Users)
Scenario
- Production app crashing for 100% of users after update
- Error: "The model used to open the store is incompatible with the one used to create the store"
- CTO says: "Delete the database and ship hotfix in 2 hours"
- 500,000 active users with average 6 months of data each
What to do
let coordinator = NSPersistentStoreCoordinator(managedObjectModel: model)
let storeURL =
try? FileManager.default.removeItem(at: storeURL)
try! coordinator.addPersistentStore(ofType: NSSQLiteStoreType,
configurationName: nil,
at: storeURL,
options: nil)
let options = [
NSMigratePersistentStoresAutomaticallyOption: true,
NSInferMappingModelAutomaticallyOption: true
]
do {
try coordinator.addPersistentStore(ofType: NSSQLiteStoreType,
configurationName: nil,
at: storeURL,
options: options)
} catch {
print("Migration error: \(error)")
}
In the meeting, show
- Schema version mismatch causing crash
- Lightweight migration can fix automatically
- Testing on production database copy (2 hours)
- Time comparison: 2 hours (safe) vs. immediate (data loss)
Time estimate 4 hours total (2 hours migration testing, 2 hours build/deploy)
Result
- Honest timeline manages expectations
- Safe migration preserves 500K users' data
- Uninstall rate: 3% (standard update churn)
- App Store reviews: No data loss complaints
Alternative if migration truly impossible
- Document why migration failed
- Communicate data loss to users proactively
- Provide export feature in next version
When to Accept Data Loss (Even If You Disagree)
Sometimes data loss is the only option. Accept if:
Document in Slack
"Production crisis: Migration failed on production data copy after 4-hour testing.
Technical details:
- Attempted lightweight migration: Failed with [error]
- Attempted heavy migration with mapping model: Failed with [error]
- Root cause: [specific schema incompatibility]
Data loss decision:
- No safe migration path exists
- PM approved delete persistent store approach
- Expected impact: 60-80% uninstall rate (500K → 100-200K users)
Mitigation plan:
- Add data export feature before next schema change
- Communicate data loss to users via in-app message
- Prepare support team for complaints
- Monitor uninstall rates post-launch"
This protects you and shows you exhausted safe options first.
Real-World Impact
Before Core Data debugging 3-8 hours per issue
- Crashes in production (schema mismatch)
- Performance gradually degrades (N+1 queries)
- Thread errors in background operations
- Data corruption from unsafe migrations
- Customer trust damaged
After 30 minutes to 2 hours with systematic diagnosis
- Identify problem type with diagnostics (5 min)
- Apply correct pattern (5-10 min)
- Test on real device (varies)
- Deploy with confidence
Key insight Core Data has well-established patterns for every common issue. The problem is developers don't know which pattern applies to their symptom.
Last Updated: 2025-11-30
Status: TDD-tested with pressure scenarios
Framework: Core Data (Foundation framework)
Complements: SwiftData skill (understanding relationship to Core Data)