# Migration Tools Comparison for Go + sqlc + pgx

## Quick Comparison

| Feature | Goose | golang-migrate | Alembic (Python) |
|---------|-------|-----------------|------------------|
| **Language** | Go | Go | Python |
| **SQL Migrations** | ✅ | ✅ | ✅ |
| **Go Migrations** | ✅ | ❌ | ❌ |
| **Embedded Support** | ✅ | ✅ | ❌ |
| **CLI** | ✅ | ✅ | ✅ |
| **Library** | ✅ | ✅ | ✅ |
| **Rollback** | ✅ | ✅ | ✅ |
| **Transactions** | ✅ | ✅ | ✅ |
| **Learning Curve** | Easy | Easy | Medium |
| **Community** | Large | Large | Large |
| **Maintenance** | Active | Active | Active |

## Goose (Recommended for TraceRTM)

### Pros
- ✅ Native Go support
- ✅ Can write migrations in Go functions
- ✅ Embedded migrations (compile into binary)
- ✅ Simple CLI
- ✅ Works perfectly with pgx
- ✅ No external dependencies
- ✅ Supports environment variable substitution

### Cons
- ❌ Slightly larger binary size
- ❌ Less flexible than Alembic for complex logic

### Best For
- Go projects with sqlc + pgx
- Projects needing embedded migrations
- Teams wanting Go-only tooling

## golang-migrate

### Pros
- ✅ Lightweight
- ✅ Multiple sources (file, GitHub, S3, GCS)
- ✅ Embedded migrations
- ✅ Simple API
- ✅ Works with pgx

### Cons
- ❌ SQL-only (no Go migrations)
- ❌ Less feature-rich than Goose
- ❌ Smaller community

### Best For
- Simple SQL-only migrations
- Projects needing remote migration sources
- Minimal dependencies

## Alembic (Python - Current Setup)

### Pros
- ✅ Very powerful
- ✅ Auto-generate migrations
- ✅ Complex logic support
- ✅ Mature ecosystem

### Cons
- ❌ Python dependency
- ❌ Separate from Go codebase
- ❌ Harder to integrate with Go
- ❌ Overkill for simple migrations

### Best For
- Python projects
- Complex schema evolution
- Teams with Python expertise

## Recommendation for TraceRTM

**Use Goose** because:

1. **Native Go Integration**: Matches your Go backend
2. **sqlc Compatibility**: Works seamlessly with sqlc
3. **pgx Support**: Direct pgx integration
4. **Embedded Migrations**: Compile migrations into binary
5. **Go Migrations**: Can write complex logic in Go
6. **Simple CLI**: Easy to use and understand
7. **No Python Dependency**: Keep stack pure Go

## Migration Strategy

### Structure
```
backend/
├── migrations/
│   ├── 00001_init.sql
│   ├── 00002_add_profiles.sql
│   ├── 00003_add_indexes.sql
│   └── 00004_add_functions.go
├── main.go
└── internal/
    └── db/
        └── migrations.go
```

### Workflow
1. Create migration: `goose create migration_name sql`
2. Edit migration file
3. Test locally: `goose up`
4. Commit to git
5. Deploy: `goose up` on production

### Integration Points
- **main.go**: Run migrations on startup
- **CI/CD**: Run migrations before deployment
- **Rollback**: Use `goose down` if needed
- **Status**: Check with `goose status`

## Next Steps

1. Install Goose
2. Create migrations directory
3. Move existing schema to migrations
4. Integrate with main.go
5. Test locally
6. Deploy to Supabase

