https://github.com/anilerc/cqrs-design-pattern-kafka-spring

Core Command-Query Responsibility Segregation design pattern implementation with Apache Kafka for processing events and Java/Spring for microservices.
https://github.com/anilerc/cqrs-design-pattern-kafka-spring

cqrs cqrs-pattern event-driven-architecture java kafka spring spring-boot

Last synced: about 2 months ago
JSON representation

Core Command-Query Responsibility Segregation design pattern implementation with Apache Kafka for processing events and Java/Spring for microservices.

• Host: GitHub
• URL: https://github.com/anilerc/cqrs-design-pattern-kafka-spring
• Owner: anilerc
• Created: 2023-12-21T15:26:16.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-12-21T17:25:12.000Z (about 1 year ago)
• Last Synced: 2023-12-21T20:18:31.351Z (about 1 year ago)
• Topics: cqrs, cqrs-pattern, event-driven-architecture, java, kafka, spring, spring-boot
• Language: Java
• Homepage:
• Size: 179 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
### CQRS System Design with Java/Spring and Apache Kafka

![System design chart](/representation.png)

### Understanding CQRS

CQRS stands for Command Query Responsibility Segregation. This pattern divides an application into two parts: the Command side and the Query side. The Command side handles tasks that modify data (create, update, delete), while the Query side manages data retrieval (read). This separation offers numerous advantages, particularly in microservices architecture.

### Advantages of CQRS

##### 1. Improved Performance and Scalability

Separation of Concerns: By separating read and write operations, CQRS allows for the optimization of each operation independently. This separation means that read and write databases can be scaled according to their specific load.

Load Balancing: In systems with different read and write load, CQRS allows for balancing these loads more effectively. For instance, a system with heavy read operations can have more resources dedicated to the query side.

##### 2. Enhanced Flexibility and Maintainability

Technology Agnostic: Each side (Command and Query) can use technologies best suited for their purpose. For example, a document-based NoSQL database might be ideal for reads, while a relational database could be preferred for writes.

Simplified Complex Systems: CQRS is beneficial in systems with complex business logic, as it allows developers to focus on either command or query responsibilities, reducing the cognitive load.

### My Implementation with Spring + Kafka & how it works

Command Side: When a command is issued (like creating or modifying data), it is processed by the command model. The resulting events (e.g., data updated, item created) are published to a Kafka topic.

Event Processing: Apache Kafka acts as the event backbone. It ensures that events are durably stored and facilitates the asynchronous communication between microservices.

Query Side: The query microservices subscribe to relevant Kafka topics. When an event is consumed, it updates the query database according to the incoming event type (UPDATE, CREATE, DELETE).

### Conclusion

CQRS pattern provides a powerful architecture and separation of concerns for building scalable, maintainable, and flexible applications; capable of tailoring different parts for different workloads. 

It addresses the challenges of handling high-throughput, distributed systems, and complex domain models.