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Are There Books Similar To 'Designing Data-Intensive Applications'?

2026-02-22 12:16:01 292

4 Answers

Kyle

2026-02-25 06:44:44

You bet there are! I’d recommend 'Building Microservices' by Sam Newman if you want to explore how data-intensive principles apply to service architecture. It’s less about raw databases and more about scaling systems—kinda like the next logical step after Kleppmann’s foundational work. 'Site Reliability Engineering' from Google’s team is another heavyweight, especially for ops-focused folks. And don’t overlook 'Data and Reality' by William Kent; it’s older but tackles data modeling in this philosophical way that still feels fresh. These all sit on my shelf right next to 'Designing Data-Intensive Applications', dog-eared and covered in sticky notes.

Zachary

2026-02-25 08:48:20

Oh, absolutely! 'Designing Distributed Systems' by Brendan Burns gives Kubernetes-flavored insights that pair well with Kleppmann’s material. For a broader take, 'Systems Performance' by Brendan Gregg is my go-to for deep dives into Linux internals—it’s not just about data but how systems breathe. And 'Big Data' by Nathan Marz nails the Lambda Architecture stuff. Funny how these books feel like different lenses on the same giant, chaotic system we call modern computing.

Andrew

2026-02-27 21:27:59

If you're craving more books like 'Designing Data-Intensive Applications', you're in luck! One that immediately comes to mind is 'Database Internals' by Alex Petrov. It dives deep into storage engines and distributed systems with the same technical rigor but feels more accessible somehow. I once spent a whole weekend geeking out over its explanation of B-trees—it’s that kind of book.

Another gem is 'Streaming Systems' by Tyler Akidau, Slava Chernyak, and Reuven Lax. It focuses on real-time data processing, which complements Martin Kleppmann’s work beautifully. For a lighter but still insightful read, 'The Pragmatic Programmer' by Andrew Hunt and David Thomas offers timeless wisdom on software engineering, though it’s broader in scope. Honestly, each of these left me with that same 'aha' feeling I got from Kleppmann’s book.

Grace

2026-02-28 21:19:48

Totally! 'Making Sense of Stream Processing' by Martin Kleppmann himself is a great follow-up if you loved his style. For a hands-on approach, 'Understanding Distributed Systems' by Roberto Vitillo breaks things down with clear examples—I actually used his Redis cluster demo at work last month. 'Data Intensive Text Processing with MapReduce' by Jimmy Lin and Chris Dyer is niche but gold for big-data folks. And if you’re into the theoretical side, 'Readings in Database Systems' (the 'Red Book') is a classic anthology. It’s wild how these books build on each other, like pieces of a giant puzzle.

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