mgo

Pros of mgo

• Original, well-established MongoDB driver for Go
• Extensive documentation and community support
• Stable API with long-term compatibility

Cons of mgo

• No longer actively maintained
• Lacks support for newer MongoDB features
• May have unresolved bugs or performance issues

Code Comparison

mgo:

session, err := mgo.Dial("localhost")
if err != nil {
    panic(err)
}
defer session.Close()

globalsign/mgo:

session, err := mgo.DialWithInfo(&mgo.DialInfo{
    Addrs: []string{"localhost"},
    Timeout: 60 * time.Second,
})
if err != nil {
    panic(err)
}
defer session.Close()

Key Differences

• globalsign/mgo is a fork of the original mgo project
• globalsign/mgo provides active maintenance and bug fixes
• globalsign/mgo includes support for newer MongoDB features
• globalsign/mgo offers improved performance in some areas
• globalsign/mgo maintains API compatibility with the original mgo

Recommendation

For new projects or those requiring support for recent MongoDB features, globalsign/mgo is generally recommended due to its active maintenance and ongoing improvements. However, existing projects using mgo may continue to use it if they don't require newer features and are satisfied with its stability.

Pros of mongo-go-driver

• Official MongoDB driver with better long-term support and updates
• Implements more recent MongoDB features and optimizations
• Better performance, especially for large datasets and complex operations

Cons of mongo-go-driver

• Steeper learning curve and more complex API compared to mgo
• Requires more boilerplate code for basic operations
• May require significant refactoring when migrating from mgo

Code Comparison

mgo:

session, err := mgo.Dial("mongodb://localhost")
c := session.DB("test").C("users")
err = c.Insert(bson.M{"name": "John", "age": 30})

mongo-go-driver:

client, err := mongo.Connect(context.TODO(), options.Client().ApplyURI("mongodb://localhost"))
collection := client.Database("test").Collection("users")
_, err = collection.InsertOne(context.TODO(), bson.M{"name": "John", "age": 30})

The mongo-go-driver code is more verbose but provides better context handling and more flexibility. mgo offers a simpler API for basic operations but lacks some advanced features and optimizations present in the official driver.

Pros of sqlx

• Supports multiple SQL databases (MySQL, PostgreSQL, SQLite)
• Provides a more flexible and SQL-centric approach
• Offers both low-level and high-level database operations

Cons of sqlx

• Requires more manual SQL query writing
• Less abstraction from underlying database structure
• May require more setup and configuration for different databases

Code Comparison

mgo example:

session, err := mgo.Dial("localhost")
c := session.DB("test").C("people")
err = c.Insert(&Person{Name: "Alice", Age: 30})

sqlx example:

db, err := sqlx.Connect("postgres", "user=foo dbname=bar")
_, err = db.Exec("INSERT INTO people (name, age) VALUES ($1, $2)", "Alice", 30)

Summary

sqlx is a versatile SQL library supporting multiple databases, offering more flexibility but requiring more manual SQL writing. mgo is MongoDB-specific, providing higher abstraction but limited to one database type. sqlx is better suited for projects using SQL databases and requiring fine-grained control, while mgo excels in MongoDB-centric applications with simpler querying needs.

Pros of gorm

• Supports multiple databases (MySQL, PostgreSQL, SQLite, SQL Server)
• Provides a more feature-rich ORM with advanced querying capabilities
• Offers hooks for custom logic before/after database operations

Cons of gorm

• Higher learning curve due to more complex API
• Potentially slower performance for simple queries compared to mgo
• May introduce overhead for applications with basic database needs

Code Comparison

mgo example:

session, err := mgo.Dial("localhost")
c := session.DB("test").C("users")
err = c.Insert(&User{Name: "John", Age: 30})

gorm example:

db, err := gorm.Open("mysql", "user:password@/dbname")
user := User{Name: "John", Age: 30}
db.Create(&user)

Key Differences

• mgo is specifically designed for MongoDB, while gorm supports multiple SQL databases
• gorm provides a more abstracted ORM layer, whereas mgo offers a lower-level API
• mgo is generally faster for simple operations, but gorm offers more advanced features and flexibility

Pros of pg

• Supports PostgreSQL-specific features like JSON, JSONB, and array types
• Offers an ORM-like query builder for more expressive and type-safe queries
• Provides built-in connection pooling for better performance

Cons of pg

• Limited to PostgreSQL databases, unlike mgo's MongoDB support
• Steeper learning curve due to more complex API and ORM-like features
• Less mature and smaller community compared to mgo

Code Comparison

mgo example:

session, err := mgo.Dial("localhost")
c := session.DB("test").C("users")
err = c.Insert(&User{Name: "John", Age: 30})
var result User
err = c.Find(bson.M{"name": "John"}).One(&result)

pg example:

db := pg.Connect(&pg.Options{Addr: "localhost:5432"})
user := &User{Name: "John", Age: 30}
_, err := db.Model(user).Insert()
err = db.Model(user).Where("name = ?", "John").Select()

Both libraries provide similar functionality for basic database operations, but pg offers a more SQL-like syntax and stronger typing. mgo uses BSON for queries, while pg uses a query builder approach. pg's API is more verbose but potentially more flexible for complex queries.