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Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems (2017)

by Martin Kleppmann

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451955,102 (4.72)None
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?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. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.Peer under the hood of the systems you already use, and learn how to use and operate them more effectivelyMake informed decisions by identifying the strengths and weaknesses of different toolsNavigate the trade-offs around consistency, scalability, fault tolerance, and complexityUnderstand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures… (more)
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This book covered data intensive systems very well with lots of great explanations of different approaches and guidance of when to use different otions. It delved to a very low level of detail in many areas. It is not an easy read and I would treat it more as a reference book to come back to when there is a problem I am trying to address. ( )
  gianouts | Jul 5, 2023 |
LSM-trees, SSTables, row- and column-oriented databases, multi-leader replication, conflict resolution for writes a in distributed environment, data balancing - if terminologies like the above interest you, then this book will interest you.

It's a pretty big book - around 600 pages, but each chapter kept providing more and more information about what options to go about while architecting a solution. ( )
  nmarun | Sep 8, 2022 |
A must read guide for anyone interacting with a database. ( )
  eatonphil | May 8, 2022 |
This book is dense. It's taken me THREE YEARS to get through it, but I'm so glad I did. Kleppmann builds up a complete picture of handling data in software applications, starting from basic principles and ending with a tight and considered summary of where things are headed, including a thoughtful review of the ethical considerations around data capture and analysis. This is one I'm sure to find myself referring back to over and over again, and recommending to everyone I know interested in data and technology. ( )
  krtierney | May 12, 2021 |
Quite possibly the best technical book I've ever read. If you are a data infrastructure engineer, you've got to read this thing. ( )
  rsanek | Dec 30, 2020 |
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Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?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. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.Peer under the hood of the systems you already use, and learn how to use and operate them more effectivelyMake informed decisions by identifying the strengths and weaknesses of different toolsNavigate the trade-offs around consistency, scalability, fault tolerance, and complexityUnderstand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

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