The Observer vs Pub-Sub Pattern: Understanding Event Communication

This blog unpacks the differences between the in-process Observer pattern and the cross-system Publish-Subscribe (Pub/Sub) pattern. It will explore how each pattern works for event communication, their key differences (synchronous vs asynchronous, coupling, scope), and when to use which approach.

Imagine you’re building an application and something noteworthy happens – a button is clicked or new data arrives.

How do you let other parts of the system know about this event?

There are two popular approaches: the classic Observer design pattern (often used within a single app) and the Publish-Subscribe (Pub/Sub) pattern (common in distributed systems).

Both involve a form of “listener” for events, but they work in surprisingly different ways.

Many beginners (and even experienced developers) get confused about Observer vs Pub-Sub – after all, both deal with publishers and subscribers in a sense.

In this article, we’ll clarify their differences, so you’ll know exactly when to use each.

Understanding the Observer Pattern

The Observer pattern is a foundational design pattern for in-app event handling.

In this pattern, one object acts as the Subject (or Observable) and maintains a list of other objects called Observers (or listeners) that are interested in its state changes.

Whenever the subject’s state changes or an event occurs, it notifies all its observers, typically by calling a specific update method on each observer.

The observers react to the event, but importantly, the subject itself doesn’t need to know how they react – it just calls their interface. This creates a one-to-many relationship: one subject, many observers.

Think of a GUI application: a button (subject) can have multiple event listener functions (observers) attached for the “click” event.

When you click the button, it triggers all those listener callbacks.

The button knows who its listeners are (because they registered themselves), and it directly invokes them.

This mechanism is usually synchronous – meaning the subject calls each observer immediately in the same thread of execution when the event happens.

The next step in the subject’s code might wait until all observers have been notified and finished running.

That’s fine within a single application where these calls are in-memory function calls and return quickly.

Key Characteristics of Observer Pattern

It’s in-process (all observers live within the same application or process as the subject) and involves a tight coupling in the sense that the subject holds references to its observers.

Observers typically must register/unregister themselves with the subject.

However, the coupling is not too intrusive – the subject might only know the interface of observers, not their concrete implementation.

The main point is that the subject is aware of who is observing.

There’s no intermediary; the communication is direct.

This pattern shines when you have a one-to-many relationship of events to handlers inside one software component or service.

It’s a simple, straightforward solution for things like UI events, model updates (e.g., the Model-View-Observer paradigm), or any scenario where multiple parts of an application need to stay in sync with an object’s state.

Understanding the Publish-Subscribe (Pub/Sub) Pattern

The Publish-Subscribe pattern, often shortened to Pub/Sub, is an architectural pattern commonly used for cross-system or asynchronous messaging.

It can be seen as a variation of the Observer concept, but with an important twist: the inclusion of a message broker or event bus as a middleman.

In Pub/Sub, a Publisher doesn’t send events directly to specific receivers.

Instead, the publisher sends (publishes) messages to a broker (sometimes called an event bus or message queue).

Subscribers register their interest with the broker, usually by subscribing to a specific topic or channel.

The broker then relays relevant messages to all subscribers of that topic.

Crucially, the publisher and subscribers do not know about each other’s identities or existence – they are completely decoupled and communicate only through the broker.

What does this look like in practice?

Imagine a large system where different services need to react to certain events.

For example, a microservice that handles user sign-ups might publish an event “NewUserRegistered”.

Multiple other services might be interested in this (sending a welcome email, updating analytics, etc.).

In a Pub/Sub setup, the sign-up service publishes a “NewUserRegistered” message to the broker (like a topic named user.signup).

The other services subscribe to that topic and will receive the message from the broker.

The sign-up service doesn’t call them directly (in fact, it has no clue who will receive the event), and each subscribing service handles the event in its own way.

This is typically asynchronous – the publisher just hands off the message and continues on, while subscribers might process the message slightly later, potentially on different machines or at different times.

Because Pub/Sub often involves separate processes or servers, the communication is usually mediated by a message queue or event streaming system (examples include RabbitMQ, Apache Kafka, etc.).

These systems allow messages to be stored and routed, enabling features like offline handling (a subscriber can receive the event later if it was offline at the moment of publishing).

The Pub/Sub pattern is great for scaling out event communication across multiple applications or microservices, providing loose coupling (since components don’t directly depend on each other) and resilience (the broker can buffer messages and manage delivery).

The trade-off is added complexity: you need to manage the broker infrastructure, and there’s typically more overhead (like serialization of messages, network latency, etc.) compared to in-process calls.