3 Killer Event Sourcing Mistakes You Must Avoid in 2025

Event Sourcing. The pattern whispers promises of immutable audit logs, powerful analytics capabilities, and a system that can time-travel. It’s the darling of modern distributed systems and Domain-Driven Design (DDD) circles. And for good reason—when implemented correctly, it’s incredibly powerful.

But let’s be honest. For every team that successfully harnesses its power, another finds itself tangled in a web of complexity, fighting subtle bugs and scalability nightmares. The allure of a perfect, append-only log can quickly fade when you stumble into one of its many hidden traps.

As we head into 2025, the patterns and anti-patterns of Event Sourcing are more defined than ever. If you're considering this journey or are already on the path, avoiding a few critical mistakes can mean the difference between a resilient, evolvable system and a technical dead-end. Let's dive into the three killer mistakes you absolutely must avoid.

The Anemic Event: Mistake #1 - Storing State, Not Intent

This is perhaps the most common and insidious mistake. A team starts with Event Sourcing and models their events like database updates. They create generic events like OrderUpdated or CustomerChanged, and stuff a JSON blob of the new state into the payload. On the surface, it seems to work. You have a history, right?

Wrong. You have a history of state changes, but you’ve lost the most valuable piece of information: the business intent.

Why did the customer’s details change? Did they correct a typo in their name (CustomerNameCorrected), or did they get married and change their last name (CustomerLastNameChangedDueToMarriage)? Why was the product price updated? Was it a routine price increase (ProductPriceIncreased), or a temporary sale (ProductDiscountedForHolidaySale)?

These distinctions are not just semantic fluff; they are the heart and soul of your domain. When you use anemic, state-focused events, you lose this richness. Your event log becomes a cryptic changelog instead of a meaningful story of your business.

Anemic vs. Rich Events: A Quick Comparison

Consider the difference in clarity and value:

By capturing intent, your event stream becomes an invaluable asset for analytics, debugging, and understanding business processes, without needing to infer context. Your future self will thank you.

The Monolithic Monster: Mistake #2 - Building the “God” Aggregate

In Event Sourcing, the aggregate is your consistency boundary. It’s a cluster of domain objects that can be treated as a single unit. It validates commands and, if successful, produces one or more events. To ensure consistency, you typically lock an aggregate instance, process one command at a time, and append the resulting events.

The mistake? Creating a massive “God” Aggregate that tries to manage too many business concerns. Think of an Order aggregate that handles everything: initial creation, adding line items, applying discounts, processing payments, managing shipping, handling returns, and customer communication.

This leads to two major problems:

1. Concurrency Bottlenecks: If everything related to an order goes through one aggregate, you create massive contention. A customer trying to track their shipment might be blocked because a payment is being processed for the same order. Since only one command can be processed against an aggregate instance at a time, your system’s throughput grinds to a halt.
2. High Cognitive Load & Brittleness: The logic inside this monolithic aggregate becomes a tangled mess. It violates the Single Responsibility Principle, making it incredibly difficult to understand, maintain, and evolve. A small change in the returns logic could accidentally break the payment processing.

The solution is to think in terms of smaller, more focused transactional boundaries. What *really* needs to be 100% consistent in a single transaction? Perhaps an order’s total price must be consistent with its line items. But does payment processing need to be in that same transaction? Or can it be handled by a separate Payment aggregate that is triggered by an OrderPlaced event? This shift towards eventual consistency between smaller, more specialized aggregates is key to building a scalable and maintainable event-sourced system.

The Time Travel Paradox: Mistake #3 - Neglecting Event Versioning

You’ve avoided the first two mistakes. Your events are rich with intent, and your aggregates are well-defined. Your system is humming along. Six months later, the business needs a change. The CustomerRegistered event now needs to capture a source field to track marketing campaigns. Simple, right? You just add the field to your event class.

Suddenly, your system crashes. When you try to rebuild a projection or load an old aggregate, the application fails because it can’t deserialize the old CustomerRegistered events that don't have the new source field. You’ve just broken the fundamental promise of Event Sourcing: the ability to reliably replay your history.

This is the time travel paradox: your present-day code can no longer understand its own past. Ignoring event schema evolution from day one is a ticking time bomb.

Upcasting to the Rescue

The standard solution to this is event versioning and upcasting. Here’s the strategy:

• Version Your Events: From the very beginning, include a version number in your event’s metadata (e.g., "eventVersion": 1).
• Create New Versions: When a breaking change is required, you create a new event class or a new version of the existing event. For example, CustomerRegistered_v2.
• Write Upcasters: An upcaster is a small, pure function that transforms an older version of an event into a newer one. When your application reads an event from the store, it checks the version. If it encounters a CustomerRegistered_v1, it passes it through an upcaster that converts it into a CustomerRegistered_v2, perhaps by adding the source field with a default value of 'unknown'.

This ensures your application logic only ever has to deal with the latest version of an event, while preserving the original historical record perfectly. It’s extra work, but it’s non-negotiable for the long-term health of your system.

Thinking in Events, Not Just Storing Them

Event Sourcing isn't just a persistence strategy; it's a paradigm shift in how you model your software. It forces you to think about your domain in terms of a narrative of business-significant events over time.

By avoiding these three killer mistakes—anemic events, god aggregates, and a lack of versioning—you move beyond simply storing data and start building a truly robust, insightful, and future-proof system. In 2025, getting this right is what separates the success stories from the cautionary tales. Don't just store your events; make them tell a story.