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Detailed Comparison: sqlx vs. Diesel

This document provides a detailed breakdown of the trade-offs between two popular database interaction patterns in Rust. The first is a composable toolkit (sqlx + sea-query + modql), and the second is a traditional ORM (Diesel).

1. Philosophy: Toolkit vs. ORM

This is the most fundamental difference that shapes everything else.

  • The Composable Toolkit (sqlx + sea-query + modql) 🛠️

This approach involves combining specialized libraries, each with a distinct role. You are in full control of the SQL generation and execution.

  • sqlx: The async runtime and database driver. It manages the connection pool and maps database rows to your Rust structs.
  • sea-query: A type-safe query builder. Its job is to construct the raw SQL strings that sqlx will execute. It uses an Iden pattern to prevent typos in table and column names.
  • modql: A high-level abstraction layer that automates the creation of filter logic. It uses macros to translate filter structs into sea-query conditions, dramatically reducing boilerplate for APIs.

Example: You use sea-query to build the query, then sqlx to execute it.

This design patterns allows for highly dynamic table definitions based on defined schema structs the implement FromRow. In order for functionality to be unified/predictable, a Model Controller layer is required.

// store/stores/account.rs
use sea_query::{Expr, Query, PostgresQueryBuilder};

pub async fn get_by_id(db_pool: &PgPool, id: Uuid) -> Result<AccountRow, sqlx::Error> {
    let (sql, values) = Query::select()
        .from(AccountIden::Table)
        .columns([AccountIden::Id, AccountIden::Email])
        .and_where(Expr::col(AccountIden::Id).eq(id))
        .build_sqlx(PostgresQueryBuilder);

    let account = sqlx::query_as_with(&sql, values)
        .fetch_one(db_pool)
        .await?;

    Ok(account)
}

  • Diesel (An ORM) 🔌

Diesel is an Object-Relational Mapper. It's designed to map your database tables and relationships directly to your Rust code. It provides a Domain-Specific Language (DSL) to build queries in Rust, abstracting away raw SQL. Its goal is to provide compile-time guarantees that your queries are correct.

Example: You use Diesel's integrated DSL. There is no separate query builder or raw SQL.

This design pattern makes for extremely fast development of HTTP handlers, as can just define Diesel model structs and use table DSL directly in HTTP handler. There is no need to Controller layer as Diesel acts as Model Controller.

// store/stores/account.rs (if using Diesel)
use crate::schema::accounts; // Generated by Diesel CLI

pub fn get_by_id(conn: &mut PgConnection, id: Uuid) -> QueryResult<Account> {
    // The .find() method works on tables with a single primary key
    accounts::table.find(id).first::<Account>(conn)
}

2. Async Support

  • sqlx (Native Async)

sqlx is built from the ground up for async/await. Every database operation is non-blocking, making it a natural and ergonomic fit for modern async web frameworks like Axum and Actix-Web.

Example: The .await is clean and idiomatic.

async fn create_account(&self, ..., data: AccountForCreate) -> Result<AccountRow> {
    // ... build query with sea-query ...
    let account = sqlx::query_as_with(&sql, values)
        .fetch_one(&self.db)
        .await?; // Non-blocking operation
    Ok(account)
}

  • Diesel (Synchronous with Workarounds)

Diesel's core is synchronous (blocking). In an async application, a blocking call can stall the entire server. To use Diesel correctly in an async runtime, you must wrap every database call in a blocking task to offload it to a separate thread pool.

Example: The spawn_blocking call adds complexity.

use tokio::task::spawn_blocking;

async fn create_account(&self, ..., data: AccountForCreate) -> Result<Account> {
    let mut conn = self.db_pool.get()?;
    let new_account = spawn_blocking(move || {
        diesel::insert_into(accounts::table)
            .values(&data)
            .get_result(&mut conn)
    })
    .await??; // Two `?` for spawn_blocking error and diesel error
    Ok(new_account)
}

3. Dynamic Filtering & Queries

This is critical for building flexible APIs. Allowing for client defined Filters and List Options, obviously enforced by Filter Structs for each Schema type.

  • sqlx + sea-query + modql (Highly Flexible)

This stack excels at runtime query generation. The modql macro automatically translates an API request's query parameters (e.g., ?name_contains=test&limit=10) into complex sea-query conditions, which are then executed by sqlx.

Example: The modql macro generates the filtering logic for you.

// Define your filters
#[derive(FilterNodes)]
pub struct AccountFilter {
    pub name: Option<OpValsString>,
    pub email: Option<OpValsString>,
}

// modql automatically generates the code to turn the filter
// into sea-query conditions, which you can pass to a list function.
let items = store.list(&ctx, Some(filter), Some(opts)).await?;

  • Diesel (More Constrained)

Diesel's compile-time focus makes fully dynamic queries more verbose. You can't just parse a string. You must use the "boxed query" pattern to conditionally chain type-safe DSL methods for every supported filter.

Example: Each conditional filter must be manually coded.

use diesel::query_dsl::methods::BoxedDsl;

// Start with a query that can be dynamically modified
let mut query = accounts::table.into_boxed();

if let Some(name_filter) = filter.name {
    // Each filter must use the type-safe DSL
    query = query.filter(accounts::name.eq(name_filter));
}
// ... then execute
let results = query.load::<Account>(&mut conn)?;

4. Type Safety

  • sqlx (Good, Macro-Assisted)

When you use the query! or query_as! macros, sqlx connects to your database at compile time to inspect the query. It will fail to compile if your SQL is invalid. However, when using a runtime builder like sea-query, this compile-time validation of the full query is lost. The Iden pattern from sea-query still prevents typos in table/column names.

  • Diesel (Excellent, Compiler-Integrated)

    This is Diesel's biggest strength. The table! macro (generated by the Diesel CLI) creates a Rust representation of your database schema. The Rust compiler then uses this to type-check every part of your query DSL. It's almost impossible to write a query that references a non-existent column. This check happens offline, without needing a database connection.