Pros of Sea-ORM

• Async support out of the box, making it suitable for modern asynchronous Rust applications
• More flexible and adaptable to different database schemas without requiring code regeneration
• Supports multiple databases (MySQL, PostgreSQL, SQLite) with a unified API

Cons of Sea-ORM

• Generally slower performance compared to Diesel due to its runtime abstraction
• Less mature ecosystem and community support
• Steeper learning curve for developers new to ORM concepts

Code Comparison

Diesel query:

let results = users
    .filter(published.eq(true))
    .limit(5)
    .load::<Post>(&mut conn)?;

Sea-ORM query:

let results = Post::find()
    .filter(post::Column::Published.eq(true))
    .limit(5)
    .all(&db).await?;

Both ORMs provide a similar query-building experience, but Sea-ORM's async nature is evident in its use of .await. Diesel's syntax is slightly more concise, while Sea-ORM's is more explicit about column references.

Sea-ORM offers more flexibility in working with different database schemas without regenerating code, which can be advantageous in certain development scenarios. However, Diesel's static approach often results in better performance and compile-time checks.

The choice between these ORMs depends on specific project requirements, such as the need for async support, performance considerations, and the desired level of abstraction.

Pros of SQLx

• Async-first design, supporting modern asynchronous Rust programming
• Compile-time checked queries, ensuring SQL correctness at compile-time
• Support for multiple databases (PostgreSQL, MySQL, SQLite) without changing code

Cons of SQLx

• Steeper learning curve due to its more low-level nature
• Less abstraction over database operations compared to Diesel's ORM approach
• Potentially more verbose for complex queries or relationships

Code Comparison

SQLx:

let users = sqlx::query!("SELECT * FROM users WHERE active = ?", true)
    .fetch_all(&pool)
    .await?;

Diesel:

let users = users::table
    .filter(users::active.eq(true))
    .load::<User>(&connection)?;

Summary

SQLx offers a more low-level, async-first approach with compile-time query checking, while Diesel provides a higher-level ORM experience. SQLx supports multiple databases seamlessly, but may require more code for complex operations. Diesel offers a more traditional ORM interface, potentially simplifying certain tasks at the cost of less flexibility in some scenarios.

Pros of Prisma Engines

• More extensive database support, including MongoDB and CockroachDB
• Automatic database migrations and schema generation
• Powerful query API with type-safe queries and results

Cons of Prisma Engines

• Steeper learning curve due to its unique query API
• Less flexibility in raw SQL queries compared to Diesel
• Potentially higher overhead for simple applications

Code Comparison

Prisma query:

const users = await prisma.user.findMany({
  where: { age: { gte: 18 } },
  select: { name: true, email: true }
})

Diesel query:

let users = users::table
    .filter(users::age.ge(18))
    .select((users::name, users::email))
    .load::<(String, String)>(&mut conn)?;

Both Prisma and Diesel are powerful ORM tools for Rust, but they cater to different needs. Prisma offers a more comprehensive solution with automatic migrations and support for various databases, while Diesel provides a more Rust-native approach with better raw SQL integration. The choice between them depends on project requirements, database complexity, and developer preferences.

Pros of rbatis

• Supports multiple databases (MySQL, PostgreSQL, SQLite, etc.) out of the box
• Provides dynamic SQL generation with a macro-based approach
• Offers both synchronous and asynchronous APIs

Cons of rbatis

• Less mature and less widely adopted compared to Diesel
• Documentation may be less comprehensive or up-to-date
• Steeper learning curve due to its macro-heavy approach

Code Comparison

rbatis:

#[crud_table]
#[derive(Clone, Debug)]
pub struct User {
    pub id: Option<u64>,
    pub name: Option<String>,
}

let user = User { id: None, name: Some("John".to_string()) };
rb.save(&user, &[]).await?;

Diesel:

#[derive(Queryable, Insertable)]
#[table_name = "users"]
struct User {
    id: Option<i32>,
    name: String,
}

let user = User { id: None, name: "John".to_string() };
diesel::insert_into(users::table).values(&user).execute(conn)?;

Both rbatis and Diesel provide ORM functionality for Rust, but they differ in their approach and feature set. rbatis offers more flexibility with database support and dynamic SQL generation, while Diesel is more established and has a simpler learning curve. The choice between them depends on specific project requirements and developer preferences.

Pros of rust-postgres

• More lightweight and focused solely on PostgreSQL
• Provides lower-level control over database operations
• Supports asynchronous operations with tokio

Cons of rust-postgres

• Requires more manual SQL writing compared to Diesel's ORM approach
• Less abstraction for database-agnostic operations
• Steeper learning curve for developers unfamiliar with raw SQL

Code Comparison

Diesel (ORM-style query):

let results = users
    .filter(published.eq(true))
    .limit(5)
    .load::<Post>(&mut conn)?;

rust-postgres (raw SQL query):

let rows = client.query(
    "SELECT * FROM posts WHERE published = $1 LIMIT $2",
    &[&true, &5],
)?;

Diesel focuses on type-safe, ORM-style queries using Rust's type system, while rust-postgres requires writing raw SQL strings. Diesel provides more compile-time safety and abstraction, whereas rust-postgres offers more direct control over the SQL being executed.

Both libraries are well-maintained and popular choices for working with PostgreSQL in Rust. Diesel is better suited for projects requiring an ORM with database-agnostic features, while rust-postgres is ideal for developers who prefer working directly with SQL and need PostgreSQL-specific functionality.