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4820994
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
88% of respondents would recommend this to a friend
Nº de artículo:
4820994
COP 364222
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This book breaks down the internals of various databases and data processing systems, and it is great fun to explore the intelligent thinking that has gone into their design.
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What Stands Out
Comprehensive Coverage
Offers in-depth insights into the principles of building reliable data systems, making complex concepts accessible for developers and engineers looking to enhance their data architecture skills.
Practical Guidance
Provides practical examples and best practices, helping readers to apply theoretical knowledge to real-world scenarios, thus improving their ability to design and maintain robust applications.
Focus on Scalability
Emphasizes scalable solutions for data-intensive applications, enabling organizations to grow their systems efficiently while ensuring high performance and reliability under varying loads.
Detalles de producto
- Comprehensive guide by Martin Kleppmann on navigating the landscape of processing and storing data
- Learn to make informed decisions on tools and technologies for data processing and storage
- Understand trade-offs and principles around consistency, scalability, fault tolerance, and complexity
- Suitable for software engineers, software architects, and technical managers involved in building web applications or network services
- Does not cover detailed instructions on specific software packages or APIs, but focuses on fundamental principles and trade-offs
- Features a bias toward free and open source software and explores the architecture of data systems integrated into data-intensive applications
| Publisher | O'Reilly Media |
| Publication date | May 2, 2017 |
| Edition | 1st |
| Language | English |
| Print length | 614 pages |
| ISBN-10 | 1449373321 |
| ISBN-13 | 978-1449373320 |
| Dimensions | 7 x 1.25 x 9.5 inches (17.8 x 3.2 x 24.1 cm) |
| Package Weight | 3 Pound |
Who Should Buy?
-
Software Engineers
Engineers looking to build reliable, scalable systems will gain essential insights into data management and architecture.
-
Data Architects
Data architects can deepen their understanding of various data systems and improve their design approaches.
-
Technical Managers
Managers overseeing data-heavy projects will benefit from an understanding of system design and infrastructure.
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Beginner Programmers
Novices may find the content too advanced and complex without foundational knowledge in data systems.
DESCRIPCIÓN DEL PRODUCTO
About This Item
The "Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems" book is a must-have for anyone involved in e-commerce systems design and architecture. From the reliability and scalability of e-commerce systems to their maintainability, this book covers all aspects of creating data-intensive e-commerce applications. With the rapid growth of online shopping, it is crucial for businesses to build reliable e-commerce systems that can handle large volumes of data and traffic. This book provides insights into the strategies and techniques needed to ensure the dependability and availability of e-commerce systems. Scalability is another key factor in e-commerce systems.
As businesses grow, their systems must be able to handle increasing loads without compromising performance. The book delves into various approaches for designing scalable e-commerce systems and addresses the challenges that organizations may face in achieving this scalability. Maintainability is equally important in e-commerce systems. Businesses need systems that are easy to manage, update, and fix if issues arise.
This book examines best practices and techniques for building maintainable e-commerce systems, ensuring that businesses can easily make changes and improvements as necessary. In addition to reliability, scalability, and maintainability, this book covers other important aspects of e-commerce systems, including security, monitoring, optimization, recovery, and testing. It provides a comprehensive guide on how to design, implement, and manage e-commerce systems effectively. Whether you are an e-commerce systems architect, developer, or manager, this book is your ultimate resource for understanding the big ideas behind reliable, scalable, and maintainable e-commerce systems. It is packed with practical tips, design patterns, case studies, and implementation guidelines to help you build robust and high-performing e-commerce systems.
Don't miss out on this valuable resource that will take your e-commerce systems to the next level.
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Data Modeling & Design Editorial Review
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems offers profound insights into the complexities of distributed systems, making it essential for anyone in the field. It brilliantly covers how to choose the right technology for use cases, combining historical context with practical applications. Readers appreciate how it thoroughly explores subjects like scalability, durability, and the nuances between consistency models. With engaging explanations of various data systems and technologies, including Kafka and HDFS, this book not only reinforces existing knowledge but also opens up new perspectives on problem-solving in data-intensive applications. Its depth ensures even seasoned professionals find valuable takeaways.
Customer Reviews & Ratings
5589 valoraciones de los clientes
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5 estrella
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ventajas
- In-depth exploration of data system technologies
- Excellent explanations of complex concepts
- Well-structured with practical real-world examples
- Engaging writing style keeps readers interested
- Historical context enriches understanding
Contras
- Some topics may be too complex for beginners
Product Price History
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COP 364222
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características y beneficios
- Learn to make scalable data systems for apps with millions of users.
- Understand the strengths and weaknesses of various data technologies.
- Explore principles and compromises fundamental to data systems.
- Get insights on system architecture for data-intensive applications.
- Emphasizes free and open-source software for hands-on learning.
- Tailored for professionals familiar with web-based applications and networking.
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