CQRS and Domain Driven Design: Anemic data model for Query side

Are you tired of dealing with complex data models that seem to suck the life out of your application? Do you find yourself lost in a sea of objects and relationships, struggling to make sense of it all? If so, then it’s time to learn about CQRS and Domain Driven Design, and how they can help you create a more focused and efficient data model for your query side.

What is CQRS?

CQRS stands for Command Query Responsibility Segregation, and it’s a software architecture pattern that separates the responsibilities of handling commands (actions) from queries (read operations). In other words, CQRS is all about dividing your data model into two separate parts: one for writing data (commands) and one for reading data (queries).

The Problem with Traditional Data Models

Traditional data models often suffer from what’s known as the “anemic data model”. This is where the data model is designed to be a simple representation of the data, without any real business logic or behavior. The result is a data model that’s bloated, complex, and difficult to maintain.

The anemic data model is often characterized by:

• Large, complex objects with many properties and relationships
• Business logic scattered throughout the application
• Difficulty in understanding the data model and how it relates to the business domain

How CQRS Solves the Problem

CQRS solves the problem of the anemic data model by separating the data model into two parts: the command side and the query side. The command side is responsible for handling actions and business logic, while the query side is responsible for providing data for read operations.

The command side typically consists of:

• Commands: These are actions that are executed on the data model, such as “CreateOrder” or “UpdateCustomer”
• Command handlers: These are responsible for handling the commands and applying the business logic
• Domain model: This is the core business logic and behavior of the application, encapsulated in objects and entities

The query side, on the other hand, consists of:

• Queries: These are requests for data, such as “GetOrders” or “GetCustomerDetails”
• Query handlers: These are responsible for retrieving the data and returning it to the client
• Read model: This is a simplified data model that’s optimized for read operations

Domain Driven Design (DDD)

Domain Driven Design is a software development approach that focuses on understanding the core business domain and modeling it in code. DDD is all about creating a shared understanding of the business domain, and using that understanding to inform the design of the software.

The Core Concepts of DDD

DDD is based on several core concepts, including:

• Domain: This is the core business domain being modeled
• Context: This is the specific area of the domain being modeled, such as orders or customers
• Entities: These are objects that have identity and behavior, such as customers or orders
• Value objects: These are immutable objects that have a set of values, such as addresses or phone numbers
• Repositories: These are responsible for encapsulating the data access and providing a layer of abstraction

How DDD Relates to CQRS

DDD and CQRS are closely related, as DDD provides the foundation for understanding the business domain, and CQRS provides the architecture pattern for separating the command and query sides.

By using DDD to understand the business domain, you can create a more focused and efficient data model for your query side. This, in turn, allows you to create a more optimized read model that’s tailored to the specific needs of your application.

Creating an Anemic Data Model for the Query Side

When creating an anemic data model for the query side, the goal is to create a simplified data model that’s optimized for read operations. This means focusing on the data that’s actually needed for the queries, and ignoring the complexities of the command side.

Step 1: Identify the Queries

The first step is to identify the queries that will be executed on the read model. This involves understanding the business requirements and the data that’s needed to support those requirements.

For example, let’s say you’re building an e-commerce application, and you need to display a list of orders for a customer. The query might look like this:

SELECT o.OrderId, o.OrderDate, o.Total
FROM Orders o
WHERE o.CustomerId = @customerId

Step 2: Design the Read Model

Once you have identified the queries, you can design the read model to support those queries. This involves creating a simplified data model that’s optimized for read operations.

In our example, the read model might consist of a single object, “OrderSummary”, with the following properties:

Property	Type
OrderId	int
OrderDate	datetime
Total	decimal

Step 3: Implement the Query Handler

The final step is to implement the query handler that retrieves the data from the read model and returns it to the client.

In our example, the query handler might look like this:

public class GetOrderSummariesQueryHandler
{
    private readonly IReadModel _readModel;

    public GetOrderSummariesQueryHandler(IReadModel readModel)
    {
        _readModel = readModel;
    }

    public List<OrderSummary> Handle(GetOrderSummariesQuery query)
    {
        return _readModel.GetOrderSummaries(query.CustomerId);
    }
}

Conclusion

In conclusion, CQRS and DDD provide a powerful combination for creating a more focused and efficient data model for your query side. By separating the command and query sides, and using DDD to understand the business domain, you can create a simplified read model that’s optimized for read operations.

By following the steps outlined in this article, you can create an anemic data model for your query side that’s simple, efficient, and easy to maintain. So why wait? Start applying CQRS and DDD to your application today, and see the benefits for yourself!

Further Reading

For more information on CQRS and DDD, be sure to check out the following resources:

• CQRS by Martin Fowler
• Domain Driven Design Community
• .NET Microservices Architecture

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