Outline of Designing Data-Intensive Applications

Outline of Designing Data-Intensive Applications

A Outline of what's inside

Embark on an In-Depth Journey into the Design of Data-Intensive Applications

In this series, we’ll unravel the complexities of building systems that are reliable, scalable, and maintainable—core principles every engineer should master.

This book, Designing Data-Intensive Applications by Martin Kleppmann, is a treasure trove of insights, and I’ll be sharing my learnings through a series of articles as I read it. Here's a sneak peek at what's coming:

Part I: Core Foundations of Data-Intensive Applications

We begin with the fundamental principles that shape the design of robust systems.

  • Chapter 1: Explore Reliability, Scalability, and Maintainability—why they matter and how to achieve them effectively.

  • Chapter 2: Compare different data models and query languages to understand when and where each shines.

  • Chapter 3: Dive into storage engines, discovering how databases structure data for efficient retrieval.

  • Chapter 4: Learn about data encoding formats and the evolution of schemas over time to manage change gracefully.

Part II: Tackling the Challenges of Distributed Systems

Scaling out to multiple machines introduces unique hurdles. This section addresses these challenges head-on.

  • Chapter 5: Replication: Ensuring data availability and durability across systems.

  • Chapter 6: Partitioning/Sharding: Breaking data into manageable chunks for scalability.

  • Chapter 7: Understanding transactions to maintain consistency in distributed environments.

  • Chapter 8: A deep dive into the quirks and challenges of distributed systems.

  • Chapter 9: Achieving consistency and consensus, the holy grail of distributed computing.

Part III: Derived Data and Integration in Heterogeneous Systems

No single database can handle all use cases, and derived datasets are key in integrating diverse systems.

  • Chapter 10: The role of batch processing in transforming and deriving data.

  • Chapter 11: Stream processing as a real-time complement to batch workflows.

  • Chapter 12: Bringing it all together—strategies for building systems that are future-proof and robust.


Stay Tuned!

This series will delve into each topic, unpacking concepts and sharing actionable insights for engineers, architects, and anyone fascinated by the underpinnings of backend systems.


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Join me on this journey as I explore each chapter, distilling complex ideas into practical knowledge. Whether you're a seasoned developer or just curious about what makes modern systems tick, this series has something for you.


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