In this post, we are going to talk about a CDC-CQRS pipeline between a normalized relational database, MySQL, as the command database and a de-normalized NoSQL database, MongoDB, as the query database resulting in the creation of DDD Aggregates via Debezium & Kafka-Streams.
This article is a dive into the realms of Event Sourcing, Command Query Responsibility Segregation (CQRS), Change Data Capture (CDC), and the Outbox Pattern. Much needed clarity on the value of these solutions will be presented. Additionally, two differing designs will be explained in detail with the pros/cons of each.
So why do all these solutions even matter? They matter because many teams are building microservices and distributing data across multiple data stores. One system of microservices might involve relational databases, object stores, in-memory caches, and even searchable indexes of data. Data can quickly become lost, out of sync, or even corrupted therefore resulting in disastrous consequences for mission critical systems.
Solutions that help avoid these serious problems are of paramount importance for many organizations. Unfortunately, many vital solutions are somewhat difficult to understand; Event Sourcing, CQRS, CDC, and Outbox are no exception. Please look at these solutions as an opportunity to learn and understand how they could apply to your specific use cases.
As you will find out at the end of this article, I will propose that three of these four solutions have high value, while the other should be discouraged except for the rarest of circumstances. The advice given in this article should be evaluated against your specific needs, because, in some cases, none of these four solutions would be a good fit.