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Designing Data-Intensive Applications (The Big Ideas Behind Reliable, Scalable, and Maintainable Systems) - 9781098119065

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9781098119065
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  • Product Details

    Author:
    Martin Kleppmann, Chris Riccomini
    Format:
    Paperback
    Pages:
    670
    Publisher:
    O'Reilly Media (March 24, 2026)
    Imprint:
    O'Reilly Media
    Release Date:
    March 24, 2026
    Language:
    English
    ISBN-13:
    9781098119065
    ISBN-10:
    1098119061
    Weight:
    37.12oz
    Dimensions:
    7" x 9.19"
    File:
    TWO RIVERS-PERSEUS-Metadata_Only_Perseus_Distribution_Customer_Group_Metadata_20260317163323-20260318.xml
    Folder:
    TWO RIVERS
    List Price:
    $69.99
    Country of Origin:
    United States
    Pub Discount:
    60
    Case Pack:
    6
    As low as:
    $60.19
    Publisher Identifier:
    P-PER
    Discount Code:
    C
  • Overview

    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