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Comment by weitzj | Hacker News Reader

The book “Designing Data-Intensive Applications” by Martin Kleppman is a fantastic read with such a concise train of thought. It builds up from basics, adds another thing, and another thing.

I kept asking myself, what would happen if I were to extend on the feature currently presented in the chapter I was reading, only to find out my answers in the next chapter.

Brilliant book

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Problem with this book is: what to read after. The book is really good but leaves you with the feeling "there are some many topics I don't know yet... but all the other books out there suck". Any recommendation for someone that has already read DDIA?

Each chapter is extensively and exhaustively referenced with the source papers. How about reading them?

https://github.com/ept/ddia-references

Here is their git repository of all online references, by chapter. Seems it doesn't include papers that don't have a clear, public link. If you have the book, though, you can get the names and search for them.

I'm currently reading Distributed Systems by Tanenbaum [1]. It goes into more detail and it's more extensive. It's more outdated but the fundamentals are there.

[1]https://www.amazon.com/gp/product/1543057381/ref=ppx_yo_dt_b...

> "Designing Data-Intensive Applications” by Martin Kleppman: https://dataintensive.net/ https://g.co/kgs/xJ73FS

Yep, came here to say this.

This was truly one of the greatest, if not the greatest, book on software that I have ever read. I have read it twice at this point and fully intend to read it many more times. It is packed full of incredibly interesting information and written in a way that keeps you interested.

Not only is the main content great, but the references are numerous and open up entirely new sets of material as you progress.

And just to extend on the numorous references, this book reminded me what a time saver a good book is compared to lots of googling and blog posts.

I struggled with blog posts on raft, Byzantine fault tolerance, CAP theorem, transactions, serializable, and this book was my enlightenment

> this book reminded me what a time saver a good book is compared to lots of googling and blog posts

I had the same reaction! The information density is perfect. If anybody else loved this book and has similar recommendations, please share.

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