kist-orm
0.9.0indexedLightweight annotation-based ORM enabling code-first, compile-time generation of type-safe DAOs for SQLite, with DAO injection, query annotations and minimal runtime overhead.
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Lightweight annotation-based ORM enabling code-first, compile-time generation of type-safe DAOs for SQLite, with DAO injection, query annotations and minimal runtime overhead.
KIST ORM is a lightweight Object-Relational Mapping (ORM) framework designed for Kotlin Multiplatform, with a primary focus on Kotlin Native desktop development. It provides an annotation-based experience similar to Android Room or Spring Data JPA, specifically tailored for SQLite databases in native environments.
The goal of KIST ORM is to provide a "Code-First" developer experience for database persistence in Kotlin Native. It aims to fill the gap for developers who prefer defining entities and queries using Kotlin annotations rather than the "Database-First" approach common in other tools.
KIST ORM leverages KSP (Kotlin Symbol Processing) to generate type-safe database access code at compile time, ensuring minimal runtime overhead and maximum performance on native targets.
kist-api: Contains the core annotations (@Entity, @Dao, @Query), common interfaces, and runtime configuration classes.kist-ksp: The symbol processor that scans your code for annotated entities and DAOs to generate their concrete implementations automatically.@Entity(tableName = "users")
data class User(
@PrimaryKeyColumn("id") var id: Long,
@Column("name") var name: String
)
@Dao
interface UserDao : KistDao<User, Long> {
@Query("SELECT * FROM users WHERE name = ?")
fun findByName(name: String): List<User>
}
// Setup connection
PersistenceContext.createConnection(SqlLiteFileConfig(dbName = "app.db"))
PersistenceContext.processAnnotations()
// Inject and use
val userDao: UserDao by injectDao()
userDao.insert(User(1, "Alice"))
For more detailed information, please refer to the documentation.
Contributions are welcome! If you have suggestions or find bugs, feel free to contribute.
Note: We prefer Pull Requests (PRs) over opening new issues. Please submit a PR with your proposed changes or fixes directly.
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