Performance Tuning

Get the best performance from Kapper with these optimization strategies.

Connection Pooling

Always use connection pooling in production:

val dataSource = HikariDataSource().apply {
    jdbcUrl = "jdbc:postgresql://localhost:5432/mydb"
    username = "user"
    password = "password"
    
    // Optimize pool settings
    maximumPoolSize = 10
    minimumIdle = 5
    connectionTimeout = 20000
    idleTimeout = 300000
    maxLifetime = 1200000
}

Query Optimization

Use Prepared Statements

Kapper uses prepared statements by default, which provides:

• SQL injection protection
• Query plan caching
• Better performance for repeated queries

Batch Operations

Kapper supports batch updates using the executeAll function:

val users = listOf(
    User("Alice", "alice@example.com"),
    User("Bob", "bob@example.com"),
    // ... more users
)

connection.executeAll(
    "INSERT INTO users(name, email, age) VALUES(:name, :email, :age)",
    users,
    "name" to User::name,
    "email" to User::email,
)

Memory Management

Close Resources

Kapper handles resource cleanup automatically when using connection.use { } blocks.

Benchmarks

See our comprehensive performance benchmarks comparing Kapper with other ORMs.

Next Steps

• Performance Benchmarks - See how Kapper performs
• Database Support - Database-specific tips
• API Reference - Complete API documentation