What is CQRS (Command Query Responsibility Segregation) and when should you use it?

CQRS separates a service's data model into two distinct paths: a Command side that handles writes (state changes) and a Query side that handles reads. Each side can use a different data store, different data model, and even a different technology stack, optimised independently for its purpose.

On the Command side, commands express intent (PlaceOrder, UpdateShippingAddress) and mutate the authoritative write model. On the Query side, pre-built, denormalised read models serve specific views efficiently — for example, an order summary view that joins order, customer, and product data is materialised as a single flat document that can be served without any JOINs.

// Command side (write)
class PlaceOrderCommand { orderId, customerId, items[] }
class OrderCommandHandler {
    handle(PlaceOrderCommand cmd) {
        Order order = new Order(cmd.orderId, cmd.customerId, cmd.items);
        orderRepository.save(order);          // write to normalised DB
        eventBus.publish(new OrderPlaced(order)); // update read models
    }
}

// Query side (read)
class OrderSummaryQuery { orderId }
class OrderQueryHandler {
    handle(OrderSummaryQuery q) {
        return orderSummaryReadModel.findById(q.orderId); // pre-built view
    }
}

When to use CQRS:

• Read and write traffic profiles differ significantly (e.g., 100:1 read-to-write ratio) and require separate scaling strategies.
• Complex domain logic on the write side conflicts with simple, fast reads that need denormalised projections.
• You are using Event Sourcing (Q13), which pairs naturally with CQRS because events update separate read projections.
• The service needs to serve multiple different view shapes to different consumers (mobile, web, analytics) without a one-size-fits-all query model.

CQRS adds complexity: two models to maintain, eventual consistency between them (the read side lags the write side), and more infrastructure. It is over-engineering for simple CRUD services where a single model suffices.

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