Abstracting the reality

Let’s define the reality as the consequence of all previous Facts.

Nobody knows every fact from the past. And when we share some facts, we don’t give them the same importance. We build our reality based on the facts we believe to know, and give them some importance based on what we think do matter.

In other words, there are several realities. A reality can be based on some false facts, still it is a reality for someone. Not to be confused with the concept of truth: there is only one truth, the problem is that nobody knows it (hint: most people suppose their reality is the truth).

Building a shared abstract reality (i.e. software) is exceptionally hard.

Spaghetti Realities

It’s the point of DDD to avoid mixing those realities. It takes lots of time and analysis to understand the realities of a business. It is an iterating task. Domain experts share a reality because they share some business processes. For example someone from the marketing team will understand another colleague from the marketing. But she won’t always understand a colleague from the shipping team. They face different challenges, they use different languages: they work in different realities.

Strategic patterns from DDD help us to build context specific solution, in order to build a software matching only one reality, avoiding an unmanageable level of complexity in the shared abstraction.

How to choose a reality

Essential complexity is the solution to a problem in its purest form. Accidental complexity is when the solution we develop is more complicated than required by the problem.

In the excellent paper Out of the tar pit, Ben Moseley and Peter Marks explain how we bring technical accidental complexity in our software, especially with states, control (the order in which things happen), and volume (the size in terms of line of code).

I think we often miss the opportunity to look for accidental complexity in the domain as well. We suppose that the problem is already well understood, whereas most of the time there is room for improvements.

How to implement the reality

If we agree that the reality is the consequence of all previous Facts, it makes sense to look for an implementation where these facts are represented. Such an implementation would be easier to translate into the reality, and vice versa. Such an implementation help to describe the essence of software: it is an automated decision maker based on past facts.This implementation is already a reality

The user send a wish into the software (“I’d like to do that…)”, the software takes a decision based on its own reality (i.e. the facts it knows), and it send feedback data to the user to help her find her next wish.

Just replace the world Fact by Event, Wish with Command and User Feedback with Query to find an existing implementation for these concepts.

A few myths about CQRS

I’m happy to see that event driven architecture rises in popularity, I already explained why I believe it makes sense. But when a topic gets more traction, we hear more and more weird things. Let me try to clarify a few myths about Command and Query Responsibility Segregation (CQRS) here.


CQRS is not Events Sourcing (which is not Event Storming)

Some people understand CQRS/ES as a single architecture paradigm. It’s actually two different paradigms, even is they were brought out together .

CQRS is about segregation of the commands and the queries in a system. It is nothing but Single Responsibility Principle (SRP) apply to separate the decisions from the effects. It comes from CQS.

Event Sourcing (ES) is about storing immutable events as the source of truth to derive any state of the whole system at any time.

Both paradigms work well together (Greg Young calls them “symbiotic”). But we can do CQRS without ES, and we can do ES without CQRS.

And just because I heard the confusion a few times, Event Storming is not Event Sourcing. It is not an architecture paradigm. Event Storming is a way to crunch knowledge with the business in an event driven approach, but it is not technical at all. It is a convention to talk with other people using post-its to represent business events.


CQRS is not Eventual Consistency

Eventual Consistency is when the read model is not synchronously updated with the write model.

It could be challenging, but it’s not mandatory in a CQRS system. We can choose to keep things synchronous, when it is good enough. We can go for an asynchronous implementation when we meet performance issue.

Thus Eventual Consistency is about performance, not about CQRS.


CQRS is not noSql and/or 2 databases

When I asked Greg Young what’s CQRS, he asks me in return if I know the concept of a SQL View. A View is nothing but a projection of the data, optimized for reading. That’s the query part of the system.

Sure, we can choose to store the query part in a separate database. Yes, it could make sense to store it in a noSql database, to reduce the impedance mismatch.

But it is CQRS as soon as there is a logical separation between command and queries. The rest is just a technical choice.

vector silhouette of a girl with raised hands and broken chains

CQRS is freedom

CQRS is before all freedom in architecture.
It allows choosing if we need eventual consistency, noSql, synchronous or asynchronous validation, and so on. It’s not an extremely complex topic, only useful for Amazon or Google.

Of course, CQRS is not a silver bullet either, but so far I have seen lots of missing opportunities to use it in several domains. But I still haven’t seen a software using CQRS where they should have go for a simple CRUD system instead.


PS: I just saw Greg has written on the same subject in a  more concise and direct way 3 years ago.

PS2: If you want to know more, I’ll be talking about the synergy between CQRS, ES and DDD, at BDXIO next October the 21st