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Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity.
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
Item #: 150163906

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

Item #: 150163906

ZAR 1527

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Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity.
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What Stands Out

Comprehensive Coverage
This edition delves deeper into key concepts of data systems, enhancing understanding of complex topics like consistency and reliability to ensure robust application design.
Real-World Insights
Offers practical examples and case studies that illustrate how to tackle common challenges, making it easier for developers to apply concepts effectively in real scenarios.
Updated Content
Incorporates the latest advancements in technology and methodologies, ensuring readers are equipped with cutting-edge knowledge necessary for building scalable and maintainable applications.

Product Details

Shop Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems online at a best price in South Africa. 1098119061
Publisher O'Reilly Media
Publication date March 24, 2026
Edition 2nd
Language English
Print length 670 pages
ISBN-10 1098119061
ISBN-13 978-1098119065
Item Weight 2.52 pounds (1.14 kg)
Dimensions 7 x 2 x 9.19 inches (17.8 x 5.1 x 23.3 cm)

Who Should Buy?

Suitable For
  • Software Engineers

    Engineers looking to deepen their understanding of data systems and improve application reliability and maintainability will benefit greatly.

  • Database Administrators

    DBAs seeking to enhance their knowledge of data modeling, integration, and management strategies will find valuable insights here.

  • System Architects

    Architects involved in designing scalable and resilient systems can leverage the principles discussed to improve architecture strategies.

Not Suitable For
  • Beginners

    Newcomers to data systems may find the content too advanced and complex, lacking foundational explanations and context.

Product Description

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

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Data Modeling & Design Editorial Review

**** "Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems" (2nd Edition) has garnered attention in the software engineering community for its substantial content, providing a deep dive into vital concepts surrounding the design and management of highly effective applications. Many professionals, particularly software engineers, have hailed this book as a must-read, especially in today's evolving tech landscape, where reliability and scalability are key factors for success. However, the reception has not been completely positive. A significant number of reviewers expressed disappointment with the print quality of the book, which was criticized for being fuzzy and difficult to read. Complaints ranged from light and poorly defined text to poor formatting, such as black bars on the pages and improper alignment of the text, which detracted from the reading experience and raised concerns about the overall production quality. Users were frustrated, particularly given the book’s price point, as many felt that the quality did not meet their expectations. Despite these physical shortcomings, the Consensus remains that the actual content of the book is exceptional. Readers appreciate the depth of information and the relevance of the material in the context of contemporary software development and artificial intelligence. Overall, while the book’s material is highly regarded and essential for engineers, the print quality issues raise concerns that potential buyers should Consider. **

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Pros

  • Outstanding content relevant to today's software development landscape.
  • Highly recommended for software engineers, especially in the context of AI advancements.
  • Valuable insights into the design of reliable, scalable applications.

Cons

  • Formatting errors such as black bars and misaligned text.

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