How do microservices handle distributed data management?
In microservices architecture, distributed data management means that each service independently owns a database and handles data consistency through coordination mechanisms. Its importance lies in supporting high scalability, rapid iteration, and fault isolation, making it suitable for high-performance scenarios such as e-commerce inventory and payment systems.
Core components include the Saga pattern for handling long transactions and CQRS for separating read and write operations, characterized by event-driven architecture and eventual consistency. Applications such as order processing ensure data integration through asynchronous events, with the impact of enhancing service autonomy while introducing challenges of latency and complexity.
Processing methods: Define data boundaries, adopt Saga to coordinate steps (such as initiating transactions and compensation rollbacks), and combine message queues to implement asynchronous communication. Typical scenarios include inventory deduction and payment confirmation, with business value in enhancing system resilience and development efficiency.
