Designing Data Intensive Applications

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.

Designing Data Intensive Applications

Designing Data Intensive Applications

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

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Designing Data-Intensive Applications
Language: un
Pages: 616
Authors: Martin Kleppmann
Categories:
Type: BOOK - Published: 2017-03-16 - Publisher: "O'Reilly Media, Inc."

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
Morgan Kaufmann series in data management systems
Language: un
Pages: 562
Authors: Stefano Ceri, Piero Fraternali, Aldo Bongio, Marco Brambilla, Sara Comai, Maristella Matera
Categories: Computers
Type: BOOK - Published: 2003 - Publisher: Morgan Kaufmann

Technologies for web applications -- Data model -- Hypertext model -- Content management model -- Advanced hypertext model -- Overview of the development process -- Requirements specifications -- Data design -- Hypertext design -- Architecture design -- Data implementation -- Hypertext implementation -- Advanced hypertext implementation -- Tools for model-based
Designing Data-Intensive Applications
Language: en
Pages: 616
Authors: Martin Kleppmann
Categories: Computers
Type: BOOK - Published: 2017-03-16 - Publisher: "O'Reilly Media, Inc."

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
Architecting Data-Intensive Applications
Language: un
Pages: 340
Authors: Anuj Kumar
Categories: Computers
Type: BOOK - Published: 2018-07-31 - Publisher: Packt Publishing Ltd

Architect and design data-intensive applications and, in the process, learn how to collect, process, store, govern, and expose data for a variety of use cases Key Features Integrate the data-intensive approach into your application architecture Create a robust application layout with effective messaging and data querying architecture Enable smooth data
Data-intensive Systems
Language: un
Pages: 97
Authors: Tomasz Wiktorski
Categories: Computers
Type: BOOK - Published: 2019-01-15 - Publisher: Springer

Data-intensive systems are a technological building block supporting Big Data and Data Science applications.This book familiarizes readers with core concepts that they should be aware of before continuing with independent work and the more advanced technical reference literature that dominates the current landscape. The material in the book is structured

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