Pros of gorm

• More mature and widely adopted in the Go community
• Supports a wider range of databases and features
• Extensive documentation and community support

Cons of gorm

• Heavier and more complex API
• Potential performance overhead due to its feature-rich nature
• Steeper learning curve for beginners

Code Comparison

orm:

type User struct {
    ID   int    `orm:"primary_key"`
    Name string `orm:"size(100)"`
}

db.Create(&User{Name: "John"})

gorm:

type User struct {
    ID   uint   `gorm:"primaryKey"`
    Name string `gorm:"size:100"`
}

db.Create(&User{Name: "John"})

Key Differences

• Syntax: Both ORMs use struct tags, but with slightly different conventions
• Feature set: gorm offers more advanced features like hooks and associations
• Performance: orm may have a slight edge in raw performance due to its lighter design
• Database support: gorm supports a wider range of databases out of the box
• Community: gorm has a larger and more active community, resulting in more resources and third-party extensions

Conclusion

Choose gorm for complex projects requiring extensive features and wide database support. Opt for orm if you prefer a simpler, lightweight ORM with potentially better performance for basic operations.

Pros of sqlx

• Lightweight and close to raw SQL, offering more control and flexibility
• Supports both database-specific features and database-agnostic operations
• Provides compile-time query checking for improved safety

Cons of sqlx

• Requires more manual work for complex queries and relationships
• Less abstraction, which may lead to more boilerplate code
• Limited built-in support for schema migrations

Code Comparison

sqlx:

rows, err := db.Query("SELECT id, name FROM users WHERE age > ?", 18)
var users []User
for rows.Next() {
    var u User
    err := rows.Scan(&u.ID, &u.Name)
    users = append(users, u)
}

orm:

users = await User.objects.filter(age__gt=18).all()

Summary

sqlx is a low-level database toolkit that provides a thin layer over SQL, offering more control and flexibility. It's suitable for developers who prefer working close to the database and want to leverage database-specific features.

orm is a high-level ORM that provides a more abstract and Pythonic way of working with databases. It offers easier querying and relationship management but may sacrifice some performance and fine-grained control compared to sqlx.

The choice between the two depends on the project requirements, developer preferences, and the need for database abstraction versus direct SQL control.

Pros of sqlboiler

• Generates type-safe, performant Go code from existing database schemas
• Supports complex queries and relationships out of the box
• Provides excellent database-specific optimizations

Cons of sqlboiler

• Requires an existing database schema to generate code
• Less flexibility for defining models in code first
• Steeper learning curve for those new to code generation tools

Code Comparison

sqlboiler:

users, err := models.Users().All(ctx, db)
if err != nil {
    return err
}

orm:

var users []User
err := db.NewSelect().Model(&users).Scan(ctx)
if err != nil {
    return err
}

Key Differences

• sqlboiler generates code based on database schema, while orm allows for in-code model definition
• sqlboiler provides more database-specific optimizations, while orm offers a more generic approach
• sqlboiler's generated code is typically more verbose but offers stronger type safety
• orm has a simpler API and is easier to get started with for beginners

Use Cases

sqlboiler is ideal for projects with existing complex database schemas and a need for high performance. orm is better suited for projects that prioritize simplicity and flexibility in model definitions.

Pros of xorm

• More mature and feature-rich, with a longer development history
• Supports a wider range of databases, including MySQL, PostgreSQL, SQLite, and more
• Offers advanced features like caching and event hooks

Cons of xorm

• Larger codebase and potentially steeper learning curve
• Less focus on modern Go idioms and practices
• May have performance overhead due to its extensive feature set

Code Comparison

xorm:

engine, _ := xorm.NewEngine("mysql", "root:password@/dbname?charset=utf8")
user := new(User)
has, _ := engine.ID(1).Get(user)

orm:

db := orm.NewDatabase("mysql://root:password@localhost/dbname")
user := &User{ID: 1}
err := db.Get(ctx, user)

Additional Notes

xorm provides a more traditional ORM experience with a wide range of features, while orm focuses on simplicity and modern Go practices. orm is newer and less mature but may offer better performance and a more idiomatic Go experience. The choice between the two depends on project requirements, database support needs, and developer preferences for API design and feature set.

Pros of pg

• More mature and feature-rich, with a longer development history
• Offers both ORM and SQL builder functionality
• Better performance, especially for complex queries and large datasets

Cons of pg

• Steeper learning curve due to more extensive API
• Less idiomatic Go code, as it uses struct tags for mapping
• Limited support for non-PostgreSQL databases

Code Comparison

orm:

type User struct {
    ID   int    `orm:"primary_key"`
    Name string
}

db.Create(&User{Name: "John"})

pg:

type User struct {
    ID   int
    Name string
}

db.Model(&User{Name: "John"}).Insert()

Summary

orm is a newer, more Go-idiomatic ORM with a focus on simplicity and ease of use. It supports multiple databases but may lack some advanced features.

pg is a mature, PostgreSQL-specific ORM and SQL builder with excellent performance and a rich feature set. It offers more power and flexibility but may require more time to learn and master.

Choose orm for simpler projects or when database portability is important. Opt for pg when working exclusively with PostgreSQL and requiring advanced features or optimal performance.