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Designing Data-Intensive Applications

About Designing Data-Intensive Applications

Designing Data-Intensive Applications is an insightful book by renowned author, Martin Kleppmann. Published in 2017 by O'Reilly Media, this book delves into the realm of big data, a genre that is becoming increasingly relevant in today's digitized world. Kleppmann presents a comprehensive guide to the intricate world of data-intensive applications, providing readers with a deep understanding of the design and architecture of such systems. This book is a must-read for anyone seeking to understand the complexities of managing data in modern applications. With its publication by O'Reilly Media, a leader in technical and technology-related publishing, you can be sure that the content is accurate, relevant, and timely.

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  • Language:
  • English
  • ISBN:
  • 9781449373320
  • Binding:
  • Paperback
  • Pages:
  • 562
  • Published:
  • May 1, 2017
  • Dimensions:
  • 234x180x30 mm.
  • Weight:
  • 1056 g.
  In stock
Delivery: 3-5 business days
Expected delivery: December 26, 2024
Extended return policy to January 30, 2025
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Description of Designing Data-Intensive Applications

Designing Data-Intensive Applications is an insightful book by renowned author, Martin Kleppmann. Published in 2017 by O'Reilly Media, this book delves into the realm of big data, a genre that is becoming increasingly relevant in today's digitized world. Kleppmann presents a comprehensive guide to the intricate world of data-intensive applications, providing readers with a deep understanding of the design and architecture of such systems. This book is a must-read for anyone seeking to understand the complexities of managing data in modern applications. With its publication by O'Reilly Media, a leader in technical and technology-related publishing, you can be sure that the content is accurate, relevant, and timely.

Publishers description of Designing Data-Intensive Applications

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.

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