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    Designing Data-Intensive Applications by Martin Kleppmann Summary

    Designing Data-Intensive Applications
    Martin Kleppmann
    4.7 (10084 Reviews)
    SoftwareComputer ScienceTechnology
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    Overview of Designing Data-Intensive Applications

    The bible of modern data engineering that transformed how tech giants build systems. Complete with Tolkien-like maps and endorsed by Databricks founder Matei Zaharia, this guide reveals why the principles behind billion-user platforms haven't changed in decades.

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    “

    The only thing worse than a system failing is a system that fails silently.

    ”
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    "Reading used to feel like a chore. Now it’s just part of my lifestyle."

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    "Feels effortless compared to reading. I’ve finished 6 books this month already."

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    Categories tendance
    Self HelpCommunication SkillRelationshipMindfulnessPhilosophyInspirationProductivity
    Listes de lecture de celebrites
    Elon MuskCharlie KirkBill GatesSteve JobsAndrew HubermanJoe RoganJordan Peterson
    Collection primee
    Pulitzer PrizeNational Book AwardGoodreads Choice AwardsNobel Prize in LiteratureNew York TimesCaldecott MedalNebula Award
    Sujets en vedette
    ManagementAmerican HistoryWarTradingStoicismAnxietySex
    Meilleurs livres par annee
    2025 Best Non Fiction Books2024 Best Non Fiction Books2023 Best Non Fiction Books
    Outils d'apprentissage
    Knowledge VisualizerAI Podcast Generator
    Auteurs en vedette
    Chimamanda Ngozi AdichieGeorge OrwellO. J. SimpsonBarbara O'NeillWinston ChurchillCharlie Kirk
    BeFreed vs autres applications
    BeFreed vs. Other Book Summary AppsBeFreed vs. ElevenReaderBeFreed vs. ReadwiseBeFreed vs. Anki
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    Points clés

    1

    The Data Revolution Reshaping Our Digital World

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    Ever wondered how Google processes billions of search queries daily while your laptop struggles with a modest spreadsheet? The secret lies in data-intensive applications-systems designed to prioritize data over computation. These sophisticated architectures form the backbone of our digital economy, enabling everything from instant movie recommendations to real-time fraud detection. The challenge isn't just handling massive volumes of information but doing so reliably, efficiently, and in ways that remain maintainable as systems evolve. What makes this particularly fascinating is that the principles behind these systems affect virtually every digital interaction in our daily lives, from checking social media to ordering groceries online.

    2

    The Three Pillars: Building Systems That Last

    3

    Data Models and Storage Fundamentals

    4

    Distributed Systems and Replication Strategies

    5

    Consistency Models and Consensus

    6

    Processing Paradigms: Batch and Stream

    7

    Building Integrated Systems with Ethical Responsibility