Designing Data-Intensive Applications, 2nd Edition

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

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

Author(s): Martin Kleppmann (Author), Chris Riccomini (Author)

  • Publisher finelybook 出版社: O’Reilly Media
  • Publication Date 出版日期: March 24, 2026
  • Edition 版本: 2nd
  • Language 语言: English
  • Print length 页数: 670 pages
  • ISBN-10: 1098119061
  • ISBN-13: 9781098119065

Book Description

Data is at the center of many challenges in system design today. Difficult issues such as scalability, consistency, reliability, efficiency, and maintainability need to be resolved. In addition, there’s an overwhelming variety of systems, including relational databases, NoSQL datastores, data warehouses, and data lakes. There are cloud services, on-premises services, and embedded databases. What are the right choices for your application? How do you make sense of all these buzzwords?

In this second edition, authors Martin Kleppmann and Chris Riccomini build on the foundation laid in the acclaimed first edition, integrating new technologies and emerging trends. You’ll be guided through the maze of decisions and trade-offs involved in building a modern data system, learn how to choose the right tools for your needs, and understand the fundamentals of distributed systems.

  • Peer under the hood of the systems you already use, and learn to use them more effectively
  • Make informed decisions by identifying the strengths and weaknesses of different tools
  • Learn how major cloud services are designed for scalability, fault tolerance, and consistency
  • Understand the core principles upon which modern databases are built

Editorial Reviews

About the Author

Martin Kleppmann is an associate professor at the University of Cambridge, researching and teaching distributed systems and security protocols. He co-created Automerge, was a startup founder, and a software engineer at LinkedIn, where he implemented large-scale data systems.

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下载地址

PDF, EPUB | 12 MB | 2025-12-03 |

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