Microservices Data Consistency

Patterns and strategies for data consistency

In a microservice architecture, each service has its own database, making it impossible to use ACID transactions across services. This creates challenges in ensuring data consistency. This guide covers various approaches to guaranteeing data consistency in a distributed system: the Saga pattern, Event Sourcing, CQRS, and other strategies.

Microservice Challenges

Distributed transactions: Impossible between different services

Failures: One service may be unavailable

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Temporal Discrepancies: Data May Be Unsynchronized

Idempotency: Repeated calls can cause problems

Choreography-based Saga

Frequently asked questions

What is an Orchestration-based Saga?

Orchestration-based Saga

Does a central orchestrator manage the execution of a transaction?

A central orchestrator manages the execution of the transaction.

What are the fundamentals of Event Sourcing?

Event Sourcing provides a complete, permanent record of all changes to an application’s state.

How is the Outbox Pattern implemented?

The Outbox pattern involves publishing events to a durable message broker and then asynchronously processing those events to update databases.

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