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

Front Cover
"O'Reilly Media, Inc.", Mar 16, 2017 - Computers - 616 pages

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 effectively
  • Make informed decisions by identifying the strengths and weaknesses of different tools
  • Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity
  • Understand the distributed systems research upon which modern databases are built
  • Peek behind the scenes of major online services, and learn from their architectures
 

Selected pages

Contents

Section 1
Section 2
Section 3
Section 4
Section 5
Section 6
Section 7
Section 8
Section 18
Section 19
Section 20
Section 21
Section 22
Section 23
Section 24
Section 25

Section 9
Section 10
Section 11
Section 12
Section 13
Section 14
Section 15
Section 16
Section 17
Section 26
Section 27
Section 28
Section 29
Section 30
Section 31
Section 32
Section 33
Copyright

Other editions - View all

Designing Data-Intensive Applications: The Big Ideas Behind Reliable ...
Martin Kleppmann
Limited preview - 2017
Designing Data-intensive Applications: The Big Ideas Behind Reliable ...
Martin Kleppmann
No preview available - 2017

Common terms and phrases

abort analytics Apache application code approach atomic commit B-tree batch processing cache causal change data capture Chapter client clock Computing consensus algorithms consistency consumers coordinator data model data systems data warehouse datacenter dataflow dataset derived data discussed disk distributed filesystem distributed systems distributed transactions document encoding event log example execution fault tolerance Figure graph guarantees Hadoop hash immutable Implementing in-memory input isolation level join JSON key-value leader linearizable lost updates LSM-trees machine mapper MapReduce materialized views message brokers multi-leader replication multiple network delays nodes OLTP output partitions performance PostgreSQL problem processors programming query language queue quorums record relational databases request requires scalability schema search indexes secondary indexes sequence number serializable server snapshot isolation SPARQL SSTables storage engine stored stream processing synchronous timestamp total order total order broadcast two-phase commit two-phase locking Unix workflows write skew

About the author (2017)

Martin is a researcher in distributed systems at the University of Cambridge. Previously he was a software engineer and entrepreneur at Internet companies including LinkedIn and Rapportive, where he worked on large-scale data infrastructure. In the process he learned a few things the hard way, and he hopes this book will save you from repeating the same mistakes.



Martin is a regular conference speaker, blogger, and open source contributor. He believes that profound technical ideas should be accessible to everyone, and that deeper understanding will help us develop better software.

Bibliographic information

TitleDesigning Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
AuthorMartin Kleppmann
Publisher"O'Reilly Media, Inc.", 2017
ISBN1491903104, 9781491903100
Length616 pages
Subjects ›  › 

Computers / Business & Productivity Software / Databases
Computers / Data Science / Data Modeling & Design
  
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