Command Query Responsibility Segregation (CQRS) is a design pattern that has gained popularity for its ability to enhance the scalability and maintainability of systems. However, like any powerful tool, CQRS is surrounded by several misconceptions that can lead to confusion and misimplementation. In this blog, let’s provide clarity on these misunderstood aspects.
“You’ll need separate databases for commands and queries”
One prevalent CQRS misconception is that commands and queries must run on entirely separate databases. While it's true that the responsibilities should be separated, it doesn't necessitate physically distinct databases. Whether it's within the code, database structure, or even the same table, the key is to maintain a separation of concerns in the architecture.
“CQRS can only be used with Domain-Driven Design (DDD)”
Another misconception is that CQRS is tightly coupled with Domain-Driven Design (DDD) and that both are prerequisites for Event Sourcing. Contrary to this belief, CQRS can be implemented independently of DDD. While they complement each other well, they are not interdependent. It's entirely possible to develop a CQRS based system without adhering strictly to DDD principles. Understanding that these concepts can be applied selectively based on the project's needs allows for more flexible and pragmatic solutions.
“CQRS leads to eventual consistency problems”
A common concern associated with CQRS is the perception that it introduces eventual consistency problems. The separation of commands and queries does not automatically imply an eventually consistent system. However, it's crucial to recognize that many systems inherently have eventual consistency challenges. CQRS doesn't exacerbate these issues; rather, it makes them explicit and manageable within the system's architecture.
“CQRS systems are dependent on messaging queues”
There's a misconception that CQRS systems always require messaging queues for communication between the write and read models. In reality, the use of messaging queues like RabbitMQ or Kafka depends on the system's complexity and requirements. For simpler models, different database views or storage mechanisms may suffice without the need for message queues. While queues can facilitate communication between models, they are not mandatory. The choice depends on the specific business context, and it's essential to design the system with flexibility in mind.
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