Pocket Book Reviews: Designing Data-Intensive Applications

Gosh, I wish a book would go into exacting detail about the protocols in play in modern distributed database systems. Oh wait! Look at this!

It’s essentially a practical Distributed Systems 101 in a box.

I learned about this author because his article describing how the CAP Theorem is an outdated model for understanding database tradeoffs got popular.

Sometimes, when discussing scalable data systems, people make comments along the lines of, ‘You’re not Google or Amazon. Stop worrying about scale and just use a relational database’. There is truth in that statement: building for scale that you don’t need is wasted effort and may lock you into an inflexible design. In effect, it is a form of premature optimization. However, it’s also important to choose the right tool for the job, and different technologies each have their own strengths and weaknesses. As we shall see, relational databases are important but not the final word on dealing with data.

One of the biggest inflection points in a company’s tech stack, in my opinion, is the transition from one big database to two medium-sized databases, and this book is a great place to start.

Of course, I'm pretty sure the answer is still "always use Postgres", except when it's not, at which point the answer is "then use Redis".

The original site didn't record this post's date; this one is approximate.