Intro to CQRS Pattern
Command Query Responsibility Segregation
Applications often need to balance scalability, performance, and maintainability.
One architectural pattern that helps achieve this is Command Query Responsibility Segregation (CQRS).
In this article, we are going to learn more about this pattern.
What is CQRS?
Command Query Responsibility Segregation (CQRS) is a design pattern that divides an application’s data handling into two distinct models:
Command Model: Responsible for modifying the state of the application (e.g., create, update, or delete operations).
Query Model: Responsible for retrieving and displaying data without making any changes.
The fundamental principle behind CQRS is that commands and queries have different requirements and should be handled separately to optimize performance, scalability, and maintainability.
This separation allows each model to evolve independently, use different data stores if needed, and meet distinct performance needs.
Components of CQRS
The key components of a CQRS-based system are as follows:
Command Model:
The command model processes requests that change the system state.
It encapsulates domain logic and ensures that only valid commands are executed.
Commands are imperative: They describe what the system should do, such as "CreateOrder" or "UpdateCustomerAddress".
Query Model:
The query model is focused on retrieving data efficiently.
It uses denormalized or precomputed views to speed up reads.
Queries are declarative: They describe what the system should return, such as "GetOrderById" or "ListCustomerOrders".
Event Sourcing (Optional):
While CQRS does not mandate event sourcing, the two patterns complement each other.
With event sourcing, changes to the system state are captured as a series of immutable events. These events can be replayed to build the current state or generate projections for the query model.
How does CQRS Work?
At its core, CQRS involves splitting the application into:
Command Side:
Handles operations that change the state of the system.
Processes domain logic and validations before persisting changes.
Uses write-optimized data models for efficient updates and inserts.
Query Side:
Handles read operations to retrieve and present data.
Optimized for querying, often using denormalized views for performance.
Can use a separate database or a caching layer for faster reads.
The flow of a typical CQRS implementation looks like this:
A client sends a command (e.g., "AddOrder") to the system.
The command is validated and processed by the domain model, which updates the state in the database.
The updated state triggers an event or projection that updates the query model.
When the client sends a query (e.g., "GetOrderDetails"), the query side retrieves the requested data from the query model.
Consider this before using CQRS
Complexity: CQRS introduces additional components, such as separate data models and projections, which increase system complexity. It may not be necessary for simple applications.
Eventual Consistency: In many CQRS implementations, the query side may not immediately reflect changes made on the command side, leading to eventual consistency. This can be challenging in applications that require strict consistency.
Data Synchronization: Maintaining consistency between the command and query models requires additional infrastructure, such as message brokers or event processors.
Tooling and Expertise: Implementing CQRS often requires familiarity with event sourcing, domain-driven design (DDD), and distributed systems.
Cost: Running separate data stores for reads and writes, along with the infrastructure for event processing, can increase operational costs.
👉 So - have you used the CQRS pattern?
Shoutout
Here are some interesting articles I’ve read recently:
That’s it for today! ☀️
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For CQRS, if we are using an SQL database for write replicas, can we use a NoSQL database for read replicas?"
One thing that I learned:
Any design where data is written to one table and then transformed and inserted into another table is an example of CQRS, too. If you think about it, message brokers and ETL jobs are examples of CQRS.
Coincidentally, I'm writing about the relationship between CQRS and Event Sourcing, but from a different perspective.
Thanks for sharing, Saurabh