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Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable,
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Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Paperback - 2017

by Martin Kleppmann

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This seller has earned a 4.70 of 5 Stars rating from internet customers.
4.70 / 5 (10180 total reviews)

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

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This seller has earned a 4.70 of 5 Stars rating from internet customers.
4.70 / 5 (10180 total reviews)

Readers widely praised Martin Kleppmann’s book as a comprehensive, lucid map of modern data systems, distilling complex storage and distributed-systems concepts with clear explanations and extensive references. Many called it essential reading that sharpens engineering judgment, while noting it’s not a practical cookbook: the emphasis is on principles over product-specific how-tos. Parts I–II drew the strongest acclaim; some found consensus and later chapters dense or hard to follow, and Part III felt rushed or overly text-heavy. A minority criticized the academic tone, breadth, and detail as overwhelming or mismatched with the promise of application design. Overall, it’s viewed as an authoritative, demanding reference that rewards patient readers.

Readers say this book is:
comprehensiveinsightfullucidfoundationalauthoritativedemandingdenseacademicunevenmust-read

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From the publisher

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?

In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.

  • Peer under the hood of the systems you already use, and learn how to use and operate them more effectively
  • Make informed decisions by identifying the strengths and weaknesses of different tools
  • Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity
  • Understand the distributed systems research upon which modern databases are built
  • Peek behind the scenes of major online services, and learn from their architectures

Details

  • Title Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
  • Author Martin Kleppmann
  • Binding Paperback
  • Edition Paperback
  • Pages 611
  • Volumes 1
  • Language ENG
  • Publisher O'Reilly Media
  • Publication date 2017-04
  • ISBN 9781449373320 / 1449373321
  • Weight 2.13 lbs (0.97 kg)
  • Dimensions 9.19 x 7 x 1.24 in (23.34 x 17.78 x 3.15 cm)
  • Category Computers - Data Base Management
  • Library of Congress subjects Database management, Web site development
  • Library of Congress Catalogue Number 2017471021
  • Dewey Decimal Code 005.7

About the author

Martin is a researcher in distributed systems at the University of Cambridge. Previously he was a software engineer and entrepreneur at Internet companies including LinkedIn and Rapportive, where he worked on large-scale data infrastructure. In the process he learned a few things the hard way, and he hopes this book will save you from repeating the same mistakes.



Martin is a regular conference speaker, blogger, and open source contributor. He believes that profound technical ideas should be accessible to everyone, and that deeper understanding will help us develop better software.

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Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?
In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.

Peer under the hood of the systems you already use, and learn how to use and operate them more effectively
Make informed decisions by identifying the… Read more
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This textbook, "Designing Data-Intensive Applications : The Big Ideas Behind Reliable, Scalable, and Maintainable Systems" by Martin Kleppmann, provides in-depth knowledge of designing and implementing data systems that are reliable and can scale efficiently. It contains 614 pages of information written in English. This trade paperback publication by O'reilly, Incorporated is an excellent resource for anyone interested in data design and management. The book covers topics such as data modeling, partitioning, replication, and distributed systems. It is a valuable guide for those who want to learn how to design reliable and scalable data systems.
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