Designing Data-Intensive Applications

Name: Designing Data-Intensive Applications
Brand: O'Reilly Media
SKU: 9781449373320
Price: 120.0 NZD
Availability: InStock

By Martin Kleppmann

4.71

( 9,005 ratings, 815 reviews)

Summary

Designing Data-Intensive Applications by Martin Kleppmann explores the architecture and fundamental principles behind building applications that manage, process, and store large volumes of data. It delves into data models, storage systems, and algorithms, examining their roles in efficient data processing. The book provides insights into the challenges of data-intensive systems and how to harness them for scalable, maintainable solutions.
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Format: Paperback / softback

$120⁰⁰

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Designing Data-Intensive Applications

$120⁰⁰

Book Hero Magic created this recommendation. While it's new and still learning, it may not be perfect - your feedback is welcome! IS THIS YOUR NEXT READ?

You might enjoy this book if you are interested in understanding the principles behind building scalable, reliable, and maintainable data systems. It offers insights into data architecture and design, with practical advice on handling everything from distributed systems to storage and processing, making it ideal for technology professionals and computing enthusiasts.

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.

Description

Designing Data-Intensive Applications by Martin Kleppmann is an essential guide for software engineers, architects, and data specialists wanting to deepen their understanding of designing robust, data-centric systems. This book provides a detailed exploration into the intricate world of data processing and storage, tackling the complex challenges that arise in today's data-driven environments. From scalability and consistency to reliability and maintainability, Kleppmann addresses the core issues that every modern data engineer faces.

In this thorough and practical examination of data-intensive system design, Kleppmann offers invaluable insights into the diverse array of tools and technologies available, such as NoSQL databases, stream processing engines, batch processors, and message brokers. The book educates readers on making well-informed choices for their applications by evaluating the strengths and weaknesses of each tool, effectively demystifying the buzzwords that often cloud technological decisions.

Beyond just a reference guide, this text enables readers to peer beneath the surface of the systems they use every day, equipping them with the knowledge to operate these systems more effectively. It lays out the trade-offs and considerations surrounding consistency, scalability, fault tolerance, and complexity in a clear and accessible manner.

Kleppmann also delves into the foundational research behind distributed systems, shedding light on the principles that underpin modern databases and major online services. This approach equips readers with a historical context and a deeper understanding of the architecture and design decisions that major tech companies employ.

Through real-world examples and a hands-on approach, Designing Data-Intensive Applications empowers you to build superior systems that leverage data to its fullest potential, fostering innovation and efficiency in your applications. Whether you're building data pipelines, integrating new services, or refining existing infrastructure, this book serves as a trusted companion in navigating the complexities of data-oriented design.

Book Hero Magic summarised reviews for this book. While it's new and still learning, it may not be perfect - your feedback is welcome! HOW HAS THIS BEEN REVIEWED?

Designing Data-Intensive Applications by Martin Kleppmann is widely praised for its comprehensive exploration of modern data systems architecture. Reviewers commend its clear, insightful explanations of complex topics like distributed systems, consistency models, and data indexing. The book is appreciated as essential reading for software engineers and architects looking to understand and effectively handle the challenges of building scalable, reliable applications.