I recently found myself reflecting on how traditional database architectures struggle to capture the full story of business operations. This led me to explore Event Sourcing—a pattern that preserves every state change as immutable events. Today, I’ll guide you through implementing this powerful approach using Axon Framework with Spring Boot.

Have you ever considered what it would take to reconstruct your application’s state at any point in time?

Event Sourcing fundamentally changes how we think about data persistence. Instead of storing current state, we record every change as an event. This creates a complete audit trail and enables powerful capabilities like temporal queries and event replay.

Let me show you how Axon Framework makes this practical. First, we’ll set up our project with the necessary dependencies.

<dependency>
    <groupId>org.axonframework</groupId>
    <artifactId>axon-spring-boot-starter</artifactId>
    <version>4.8.4</version>
</dependency>

Our domain model centers around commands and events. Commands represent intentions to change state, while events represent facts that have already occurred.

public class CreateOrderCommand {
    @TargetAggregateIdentifier
    private final String orderId;
    private final String customerId;
    
    public CreateOrderCommand(String orderId, String customerId) {
        this.orderId = orderId;
        this.customerId = customerId;
    }
}

The Order aggregate handles these commands by applying events. Notice how we rebuild state by replaying events?

@Aggregate
public class Order {
    @AggregateIdentifier
    private String orderId;
    private OrderStatus status;
    
    @CommandHandler
    public Order(CreateOrderCommand command) {
        apply(new OrderCreatedEvent(command.getOrderId(), command.getCustomerId()));
    }
    
    @EventSourcingHandler
    public void on(OrderCreatedEvent event) {
        this.orderId = event.getOrderId();
        this.status = OrderStatus.CREATED;
    }
}

What happens when we need to query this data efficiently? That’s where CQRS and projections come into play.

Projections update read models based on events. This separation allows us to optimize queries independently from writes.

@Component
public class OrderProjection {
    
    @EventHandler
    public void on(OrderCreatedEvent event, @Timestamp Instant timestamp) {
        OrderView orderView = new OrderView(event.getOrderId(), event.getCustomerId(), timestamp);
        orderViewRepository.save(orderView);
    }
}

For complex business processes spanning multiple aggregates, we use sagas. These long-running processes coordinate workflows through events.

@Saga
public class OrderManagementSaga {
    
    @StartSaga
    @SagaEventHandler(associationProperty = "orderId")
    public void handle(OrderCreatedEvent event) {
        // Initiate payment process
        commandGateway.send(new ProcessPaymentCommand(event.getOrderId()));
    }
}

Testing event-sourced systems requires a different approach. Axon provides excellent testing support.

@SpringBootTest
class OrderAggregateTest {
    
    @Autowired
    private FixtureConfiguration fixture;
    
    @Test
    void testOrderCreation() {
        fixture.givenNoPriorActivity()
               .when(new CreateOrderCommand("order1", "customer1"))
               .expectSuccessfulHandlerExecution()
               .expectEvents(new OrderCreatedEvent("order1", "customer1"));
    }
}

Performance considerations become important as your event store grows. Snapshotting helps optimize aggregate loading.

@Configuration
public class SnapshotConfig {
    
    @Bean
    public SnapshotTriggerDefinition snapshotTriggerDefinition(
        Snapshotter snapshotter) {
        return new EventCountSnapshotTriggerDefinition(snapshotter, 50);
    }
}

When implementing event sourcing, remember that events are immutable facts. Design them carefully, as they become your source of truth.

What challenges might you face when migrating an existing application to this architecture?

Event sourcing requires a mindset shift. Instead of asking “what is the current state?” we ask “what sequence of events led to this state?” This perspective change unlocks powerful capabilities but also introduces complexity.

I encourage you to start with a bounded context where auditability and temporal queries provide clear business value. The investment in learning this pattern pays dividends in maintainability and business insight.

I’d love to hear about your experiences with event-driven architectures. What use cases are you considering for Event Sourcing? Share your thoughts in the comments below, and if you found this guide helpful, please like and share it with your colleagues.