ddia/en-us

Designing Data-Intensive Applications

—— The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

Martin Kleppmann

The en-us version only includes intro, summary, references of all chapters to protect the intellectual property of author and publisher.

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Technology is a powerful force in our society. Data, software, and communication can

be used for bad: to entrench unfair power structures, to undermine human rights, and to protect vested interests. But they can also be used for good: to make underrepresented people’s voices heard, to create opportunities for everyone, and to avert disasters. This book is dedicated to everyone working toward the good.

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Computing is pop culture. [...] Pop culture holds a disdain for history. Pop culture is all about identity and feeling like you’re participating. It has nothing to do with cooperation, the past or the future—it’s living in the present. I think the same is true of most people who write code for money. They have no idea where [their culture came from].

— Alan Kay, in interview with Dr Dobb’s Journal (2012)

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Table of Contents

Preface

Part I: Foundations of Data Systems

• 1. Trade-offs in Data Systems Architecture
• 2. Defining Nonfunctional Requirements
• 3. Data Models and Query Languages
• 4. Storage and Retrieval
• 5. Encoding and Evolution

Part II: Distributed Data

• 6. Replication
• 7. Partitioning
• 8. Transactions
• 9. The Trouble with Distributed Systems
• 10. Consistency and Consensus

Part III: Derived Data

• 11. Batch Processing
• 12. Stream Processing
• 13. Do the right thing

Glossary

Colophon