First of all, if you just stumbled across this article without having read the predecessor, I highly recommend taking a look at my previous article, Beyond Anemic Domain Models: Bridging the Gap Between Data and Behavior. It sets the stage for much of what we’ll unravel today. Now let me take you back to 2013 for a brief moment. At that time I was working in my company and we were entrusted with the development of a software that had some really complicated requirements. After several brainstorming sessions and countless cups of coffee, my team and I felt that CQRS (Command Query Responsibility Segregation) would do justice to the project. Without delving too much into CQRS here (I promise to explore it in another write-up), this particular endeavor was my gateway to understanding and harnessing the immense power of aggregates in DDD. That project was a defining moment, reminding me that the right design patterns can make all the difference. So, with that bit of nostalgia out of the way, let’s dive into the heart of today’s topic: Aggregates and Entities in Domain-Driven Design. Buckle up and join me on this insightful journey! Setting the Stage: Entities First, it’s essential to understand entities in the context of DDD. Remember, DDD is all about modeling complex software systems in a way that aligns with the real-world domain of the problem. So, what role do entities play in this? Entities, at their core, are unique objects. They possess a distinct identity that runs through their lifecycle, irrespective of changes in their attributes. To put it in simpler terms, think of entities as the main characters in a story. They evolve, experience different events, but their essence — their identity — remains unchanged. In our banking context, a BankAccount is a classic example of an entity. No matter how many transactions are made, no matter how the balance fluctuates, the BankAccount’s identity remains consistent.
