Command-Query Responsibility Segregation (CQRS)
A guide to streamlining your commands and optimizing your queries.
The CQRS (Command Query Responsibility Segregation) Pattern is a software design and architecture approach that distinguishes between read and write operations. In this pattern, commands (writes) are used to change the state of an application, while queries (reads) are used to retrieve data without altering the state.
Implementing CQRS offers numerous benefits:
- By separating read and write operations, different teams can focus on each aspect, leading to clearer and more maintainable code.
- Since write operations are typically less frequent than read operations, resources can be scaled independently based on the demand. For example, in an e-commerce site, users spend more time browsing (reading) than making purchases (writing to the database).
- Each operation (read or write) can have its own level of protection, allowing for fine-grained control over who can access or modify data.
Context and problem
Let’s see what kind of issues you can solve with this design pattern, along with a few examples.
In both modern and legacy systems, you’ll often find legacy architectural patterns that rely on the same data model (or DTO) to query and update data. When you’re working with a CRUD-only system, this can be great, but as it matures and becomes more complex, it can become a disaster.
Let’s consider scenarios where the number of fields differs between read and write operations. Implementing the CQRS pattern allows us to split the DTO, leading to performance improvements and reduced complexity.
For instance, consider a domain application (web-app) that deals with complex and aggregate objects and requires handling multiple concurrent operations. By restructuring the application using the CQRS pattern, it can be made more performant and scalable.
Another example is when an application needs to process a large volume of data in real-time. Using a single database, table, or DTO for both read and write operations can lead to inconsistent data and potential issues like database deadlocks or conflicting operations. Adopting the CQRS pattern helps avoid these problems by separating read and write concerns.
Implementation and considerations
To apply the CQRS pattern in application development, we start by dividing the current domain model or DTO into separate models for queries and commands. These models are managed separately to ensure that a single task can either read or write, but not both.
Commands represent actions with task-based operations, like “add item to shopping cart” or “checkout order.” They are responsible for writing to the databases.
Queries, on the other hand, are focused on reading data and never modify the database. They always return JSON data with DTO objects, allowing for the isolation of commands and queries.
By dividing tasks into distinct teams, we can easily adapt to user requirement changes and separately scale, optimize, and evolve each aspect of the application.
For a full implementation of the CQRS pattern, we have to separate the database load for read and write operations, ensuring that changes in data remain consistent. We can do this by:
- Separating read and write models (DTOs) only.
- Separating read and write models (DTOs) and databases.
In this approach, CRUD operations are divided into two separate DTOs or models. This allows us to tailor each DTO or model to specific requirements. The write models are like database tables and domain entities, while read models may include additional fields. Additionally, performing command operations becomes easier as you can adopt an event-driven approach to handle higher loads.
But there may be a potential problem. When accessing the same table in the same database, a deadlock situation can occur, slowing down the response time for read operations. To address this, we have to segregate the database as well.
In this setup, you can see that operations are separated using different databases. You can organize records in the read database based on your requirements. However, there’s a challenge: you need to ensure consistency between both databases, which may require extra effort.
In a microservice architecture, these two operations can be divided into two different services.
To maintain consistency between the read and write databases, you need to pass each write command event from the application to ensure that the read user gets the updated data. The source of events is the write database, which triggers these events or pushes messages to a message broker for the read database to process and update accordingly.
You can also use a database replication strategy to update the read database.
The benefits of using the database segregation approach include:
- Scaling: By shifting the query operation burden from the write database to the read database, scalability for accessing combined data can be enhanced if a single database struggles to handle the query load.
- Performance: With different schemas for the write and read databases, you can independently design and optimize them for better performance.
When using the CQRS pattern, keep these points in mind:
- Maintenance: When implementing CQRS, it is important to note that there will be a need to handle and update two separate database entities instead of just one. This means that any changes made in one entity must be replicated in the other to ensure consistency and reliability in the application, which may require more maintenance compared to using a single database.
- Risk: The data in two databases must be replicated and updated. One potential risk is that, because of synchronization problems, the querying database may become out-of-date or incorrect.
- Eventual consistency: Users may experience some lag in updates due to database synchronization. In a microservices architecture, this lag is expected and often accepted for long-term data consistency.
- Synchronization solution: Whichever process you select, tracking synchronization problems and replaying incorrect events will need a complex implementation.
- Event log: To identify issues related to out-of-date or inaccurate data, you must keep logs for every event and reprocess data to keep them in sync.
- Security: Data security can be managed separately for reading and writing, providing more control and flexibility.
Conclusion
The CQRS design has many applications, so you should try to implement it. Depending on the application's requirements, you can, for instance, mix two patterns:
- CQRS and Mediator
- CQRS and Event Sourcing
- CQRS and DDD(Domain Driven Development)
Even with these advantages, you should use CQRS with extreme caution. While it can enhance the separation of concerns, improve scalability, and enable better performance, it also comes with increased system complexity and can impact output. Therefore, even if CQRS is a useful pattern to have in your toolkit, you should apply it judiciously. Misusing it can lead to the removal of crucial components and create challenges in the application’s design and maintenance.
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