Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

Designing Data-Intensive Applications

The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

2015 • 611 pages

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Average rating4.6

15

Want to know how the best software engineers and architects structure their applications to make them scalable, reliable, and maintainable in the long term? This book examines the key principles, algorithms, and trade-offs of data systems, using the internals of various popular software packages and frameworks as examples. Tools at your disposal are evolving and demands on applications are increasing, but the principles behind them remain the same. You'll learn how to determine what kind of tool is appropriate for which purpose, and how certain tools can be combined to form the foundation of a good application architecture. You'll learn how to develop an intuition for what your systems are doing, so that you're better able to track down any problems that arise.

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One of the best books that I've read on the topic for industry,
Many valuable lessons in there.

January 15, 2023

A broad overview of both problem space and solution space, covering use cases and concepts of data-intensive & distributed systems with relevant examples. Perfect if you want to see the bigger picture and understand the “whys” of solutions and tradeoffs.

August 22, 2021

Packed full of straightforward, immediately applicable information for data professionals. I thought it got a bit in the weeds at the end but that might have been my own fatigue.

January 18, 2022

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