Overview
Separate read and write operations
CQRS Pattern
1 implementations available
When to Use
- When you need to abstract data access logic
- When you want to make your code testable
- When you need to support multiple data sources
- When you want to decouple business logic from infrastructure
Available Implementations
Basic Example
// CQRS Pattern implementation example
// This shows the basic structure of cqrs pattern in Fastify
// Define your interface
interface IRepository {
findAll(): Promise<T[]>;
findById(id: string): Promise<T | null>;
create(data: CreateDto): Promise<T>;
update(id: string, data: UpdateDto): Promise<T>;
delete(id: string): Promise<void>;
}
// Implement the pattern
class CQRSRepository implements IRepository {
async findAll(): Promise<T[]> {
// Implementation
}
async findById(id: string): Promise<T | null> {
// Implementation
}
async create(data: CreateDto): Promise<T> {
// Implementation
}
async update(id: string, data: UpdateDto): Promise<T> {
// Implementation
}
async delete(id: string): Promise<void> {
// Implementation
}
}
// Use the pattern
const repository = new CQRSRepository();
const items = await repository.findAll();
Frequently Asked Questions
What is CQRS Pattern?
Separate read and write operations. It's a well-established software design pattern that helps organize code for better maintainability and testability.
How does CQRS Pattern work with Fastify?
Fastify provides excellent support for this pattern through its dependency injection system and middleware composition.
What are the benefits?
Improved testability, separation of concerns, easier maintenance, and flexibility to change implementations without affecting business logic.
When should I avoid this pattern?
For very simple applications with minimal logic, the pattern may add unnecessary complexity. Use judgment based on project requirements.