Pros of TypeORM

• More mature and widely adopted, with a larger community and ecosystem
• Supports both Active Record and Data Mapper patterns
• Offers a CLI tool for generating migrations and running commands

Cons of TypeORM

• Heavier and more complex, with a steeper learning curve
• Can be slower due to its ORM nature and automatic query generation
• Less type-safe, especially when working with complex queries

Code Comparison

TypeORM:

@Entity()
class User {
  @PrimaryGeneratedColumn()
  id: number;

  @Column()
  name: string;
}

const users = await repository.find({ where: { name: "John" } });

Kysely:

interface User {
  id: Generated<number>;
  name: string;
}

const users = await db
  .selectFrom('user')
  .where('name', '=', 'John')
  .selectAll()
  .execute();

TypeORM uses decorators and an ORM approach, while Kysely employs a more SQL-like query builder with better type safety. TypeORM's syntax is more abstracted from SQL, whereas Kysely's is closer to raw SQL while maintaining type safety.

Pros of Sequelize

• More mature and widely adopted ORM with a larger ecosystem
• Supports a broader range of databases out of the box
• Offers built-in migration and seeding tools

Cons of Sequelize

• Steeper learning curve due to its extensive feature set
• Can be slower for complex queries compared to raw SQL
• Potential for performance overhead in large-scale applications

Code Comparison

Sequelize:

const User = sequelize.define('User', {
  name: DataTypes.STRING,
  email: DataTypes.STRING
});

const users = await User.findAll({
  where: { name: 'John' }
});

Kysely:

const users = await db
  .selectFrom('users')
  .select(['name', 'email'])
  .where('name', '=', 'John')
  .execute();

Key Differences

• Kysely is a type-safe query builder, while Sequelize is a full-featured ORM
• Kysely focuses on compile-time type safety, whereas Sequelize relies more on runtime checks
• Sequelize uses model definitions, while Kysely works directly with table structures
• Kysely offers a more SQL-like query syntax, making it easier for SQL developers to transition
• Sequelize provides more abstraction from the underlying database, which can be beneficial for complex applications but may sacrifice some performance

Both libraries have their strengths, and the choice between them depends on project requirements, team expertise, and performance considerations.

Pros of Prisma

• Powerful schema management with automatic migrations
• Rich ecosystem with extensive tooling and integrations
• Strong type safety and auto-generated TypeScript types

Cons of Prisma

• Steeper learning curve due to its unique query API
• Less flexibility for complex queries compared to raw SQL
• Potential performance overhead for some operations

Code Comparison

Prisma query:

const users = await prisma.user.findMany({
  where: { age: { gte: 18 } },
  include: { posts: true }
})

Kysely query:

const users = await db
  .selectFrom('user')
  .where('age', '>=', 18)
  .innerJoin('post', 'user.id', 'post.userId')
  .selectAll()
  .execute()

Prisma focuses on a declarative approach with its schema-first design, offering powerful features like automatic migrations and type generation. It excels in rapid development scenarios but may have limitations for complex queries.

Kysely, on the other hand, provides a more SQL-like query builder approach, offering greater flexibility for complex queries and potentially better performance for certain operations. However, it lacks some of the advanced schema management features and extensive ecosystem that Prisma provides.

The choice between the two depends on project requirements, team expertise, and the balance between development speed and query flexibility needed.

Pros of Knex

• Mature and widely adopted with a large community and ecosystem
• Supports a broader range of databases out of the box
• Offers both promise-based and callback-based APIs for flexibility

Cons of Knex

• Less type-safe compared to Kysely's TypeScript-first approach
• Query building can be more verbose and less intuitive
• Lacks some advanced features like recursive CTEs and lateral joins

Code Comparison

Knex query:

knex('users')
  .select('name', 'email')
  .where('age', '>', 18)
  .orderBy('name')
  .limit(10)

Kysely query:

db.selectFrom('users')
  .select(['name', 'email'])
  .where('age', '>', 18)
  .orderBy('name')
  .limit(10)

Both Knex and Kysely provide fluent query builders, but Kysely offers stronger TypeScript support and a more modern API design. Knex has the advantage of broader database support and a larger ecosystem, while Kysely focuses on type safety and a more intuitive query-building experience. The choice between them often depends on project requirements, TypeScript usage, and the specific database being used.

Pros of MikroORM

• Full-featured ORM with advanced features like identity map, unit of work, and lazy loading
• Supports multiple database types (SQL and NoSQL)
• Provides a rich ecosystem with CLI tools and integrations

Cons of MikroORM

• Steeper learning curve due to its complexity and feature-rich nature
• Potentially higher overhead for simpler database operations
• Less flexible for raw SQL queries compared to query builders

Code Comparison

MikroORM:

@Entity()
class User {
  @PrimaryKey()
  id!: number;

  @Property()
  name!: string;
}

const user = em.create(User, { name: 'John' });
await em.persistAndFlush(user);

Kysely:

const user = await db
  .insertInto('user')
  .values({ name: 'John' })
  .returningAll()
  .executeTakeFirstOrThrow();

MikroORM offers a more declarative approach with decorators and entity definitions, while Kysely provides a more SQL-like query building experience. MikroORM's code is more abstracted from the underlying SQL, whereas Kysely's code closely resembles the actual SQL operations.

Pros of Drizzle-orm

• Supports more databases out of the box, including SQLite and MongoDB
• Offers a more intuitive API for complex queries and joins
• Provides built-in migration tools for easier schema management

Cons of Drizzle-orm

• Less mature ecosystem and community compared to Kysely
• May have a steeper learning curve for developers new to ORM concepts
• Limited documentation and examples for advanced use cases

Code Comparison

Kysely query example:

const result = await db
  .selectFrom('users')
  .innerJoin('posts', 'users.id', 'posts.user_id')
  .select(['users.name', 'posts.title'])
  .where('users.id', '=', 1)
  .execute();

Drizzle-orm query example:

const result = await db
  .select({
    name: users.name,
    title: posts.title,
  })
  .from(users)
  .innerJoin(posts, eq(users.id, posts.userId))
  .where(eq(users.id, 1));

Both ORMs offer type-safe query building, but Drizzle-orm's API may be more intuitive for complex queries. Kysely's approach is more SQL-like, which might be preferred by developers with strong SQL backgrounds.