Designing Data-Intensive Applications

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INFORMATION

AUTHOR
Martin Kleppmann
DIMENSION
9,3 MB
FILE NAME
Designing Data-Intensive Applications.pdf
ISBN
1572315703880

DESCRIPTION

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

Difficult issues need to be figured out, such as scalability, consistency, reliability ... Designing Data-Intensive Applications Sometimes, when discussing scalable data systems, people make comments along the lines of, 'You're not Google or Amazon. Stop worrying about scale and just use a relational database'.

For example, many applications need to: Store data so that they, or another application, can find it again later (databases) Remember the result of an expensive operation, to speed up reads (caches) 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.

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