I’ve spent years building systems that handle complex business logic, and I’ve often found myself frustrated by the limitations of traditional databases. When a bug appears or a user reports an unexpected behavior, reconstructing what actually happened can feel like detective work with missing clues. This constant struggle led me to discover event sourcing, and I want to share how you can build a robust system using EventStore, Node.js, and TypeScript.

Event sourcing fundamentally changes how we think about data. Instead of storing only the current state, we capture every change as an immutable event. Think about your bank account—wouldn’t it be powerful to see not just your current balance, but every single transaction that led to it? This approach gives us a complete history and the ability to rebuild state from scratch.

Have you ever tried to debug a production issue only to find that critical data has been overwritten? With event sourcing, that problem disappears because we never update or delete events—we only append new ones. This creates a reliable audit trail that’s invaluable for compliance and troubleshooting.

Let me show you how this works in practice. Here’s a basic example comparing traditional CRUD with event sourcing:

// Traditional approach - we lose history
interface User {
  id: string;
  name: string;
  email: string;
  balance: number;
}

// Event sourcing approach - we preserve everything
interface UserCreated {
  eventType: 'UserCreated';
  data: {
    userId: string;
    name: string;
    email: string;
  };
}

interface BalanceDeposited {
  eventType: 'BalanceDeposited';
  data: {
    userId: string;
    amount: number;
    newBalance: number;
  };
}

Setting up the foundation requires careful planning. I start by creating a clear project structure that separates concerns. The infrastructure layer handles EventStore communication, while aggregates manage business logic. Projections build read models for efficient querying. This separation makes the system more maintainable and scalable.

What happens when you need to add new features months after deployment? Event sourcing makes this easier because you can create new projections from existing events without modifying the core system. Here’s how I define a base domain event:

export abstract class BaseDomainEvent {
  public readonly eventId: string;
  public readonly aggregateId: string;
  public aggregateVersion: number = 0;

  constructor(aggregateId: string, public readonly data: any) {
    this.eventId = require('uuid').v4();
    this.aggregateId = aggregateId;
  }

  abstract get eventType(): string;
}

The aggregate root serves as the guardian of business rules. It ensures that state changes follow domain logic and produces events that represent those changes. This pattern keeps your core business rules clean and testable. Have you considered how you’d handle concurrent modifications in your current system?

export abstract class AggregateRoot {
  protected _id: string;
  protected _version: number = 0;
  private _uncommittedEvents: DomainEvent[] = [];

  protected addEvent(event: DomainEvent): void {
    event.aggregateVersion = this._version + 1;
    this._uncommittedEvents.push(event);
    this.apply(event);
  }

  public loadFromHistory(events: DomainEvent[]): void {
    events.forEach(event => {
      this.apply(event);
      this._version = event.aggregateVersion;
    });
  }

  protected abstract apply(event: DomainEvent): void;
}

Connecting to EventStore requires proper configuration. I use the official Node.js client and handle connection strings securely. Error handling is crucial here—network issues or version conflicts can occur, and we need graceful recovery. How would your current system handle database connection failures?

export class EventStoreClient {
  private client: EventStoreDBClient;

  constructor(connectionString: string) {
    this.client = EventStoreDBClient.connectionString(connectionString);
  }

  async appendToStream(
    streamName: string,
    events: DomainEvent[]
  ): Promise<void> {
    const eventStoreEvents = events.map(event =>
      jsonEvent({
        type: event.eventType,
        data: event.data,
        metadata: event.metadata
      })
    );

    await this.client.appendToStream(streamName, eventStoreEvents);
  }
}

Eventual consistency is a common challenge in distributed systems. When we update a projection based on new events, there might be a slight delay before queries reflect the latest state. I handle this by designing user interfaces that acknowledge this possibility and provide appropriate feedback.

Monitoring becomes essential in production. I implement comprehensive logging and metrics to track event processing times, error rates, and projection lag. This visibility helps identify bottlenecks before they affect users. What monitoring tools are you currently using, and do they give you this level of insight?

Deployment strategies need special consideration. I use blue-green deployments to minimize downtime and ensure smooth transitions. Database migrations work differently in event-sourced systems—we typically create new projections rather than modifying existing data structures.

Building this system has transformed how I approach software design. The ability to replay events for debugging or create new read models without touching the core logic has saved countless hours. The initial investment in learning event sourcing pays dividends in maintainability and reliability.

I’d love to hear about your experiences with building resilient systems. Have you tried event sourcing in your projects? What challenges did you face? If you found this guide helpful, please share it with your team and leave a comment below—your feedback helps me create better content for everyone.