How does this skill handle read model synchronization?

It includes 'Projector' templates that listen for domain events from the write model to update the read-optimized database views automatically.

CQRS stands for Command Query Responsibility Segregation, an architectural pattern that uses separate models for updating data (Commands) and reading data (Queries).

When should I use the CQRS Implementation skill?

Use this skill when your application requires high-performance query optimization, independent scaling of read/write workloads, or when building event-sourced systems.

Does this skill support Python frameworks?

Yes, it provides implementation templates for Python, including specific patterns for FastAPI and asynchronous event handling.

CQRS Architecture Implementation

Name: CQRS Architecture Implementation
Author: wshobson

bywshobson

•

23,194

API Development

Implements Command Query Responsibility Segregation (CQRS) patterns to build scalable, high-performance backend architectures.

About

This skill provides a comprehensive framework for implementing the Command Query Responsibility Segregation (CQRS) pattern within backend systems. It enables developers to decouple data modification logic from retrieval logic, allowing for independent scaling of read and write operations. With standardized templates for command buses, query handlers, and event-driven synchronization, this skill is essential for building complex, high-performance distributed systems, event-sourced architectures, and optimized reporting models.

Key Features

Separates read and write concerns with specialized data models
Standardized Command and Query bus infrastructure
Asynchronous projector logic for read model synchronization
Production-ready FastAPI integration templates
23,194 GitHub stars
Event-sourced system design and implementation patterns

Use Cases

Scaling read-heavy applications independently from transactional writes
Optimizing complex reporting and dashboard query performance
Building event-driven microservices with high data consistency

About

Key Features

Separates read and write concerns with specialized data models
Standardized Command and Query bus infrastructure
Asynchronous projector logic for read model synchronization
Production-ready FastAPI integration templates
23,194 GitHub stars
Event-sourced system design and implementation patterns

Use Cases

Scaling read-heavy applications independently from transactional writes
Optimizing complex reporting and dashboard query performance
Building event-driven microservices with high data consistency