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

• Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
• Martin Kleppmann
• Page: 500
• Format: pdf, ePub, mobi, fb2
• ISBN: 9781449373320
• Publisher: O'Reilly Media, Incorporated

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Want to know how the best software engineers and architects structure their applications to make them scalable, reliable, and maintainable in the long term? This book examines the key principles, algorithms, and trade-offs of data systems, using the internals of various popular software packages and frameworks as examples. Tools at your disposal are evolving and demands on applications are increasing, but the principles behind them remain the same. You’ll learn how to determine what kind of tool is appropriate for which purpose, and how certain tools can be combined to form the foundation of a good application architecture. You’ll learn how to develop an intuition for what your systems are doing, so that you’re better able to track down any problems that arise.

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Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. Designing Data-Intensive Applications : The Big Ideas Behind
Designing Data-Intensive Applications : The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. Want to know how the best software engineers  The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, structure their applications to make them scalable, reliable, and maintainable in the  Big Data Enterprise Architecture: Overview | Data Intensive
Data ingestion in a Big Data system is a hard task, once you get In order to design a complete Data Ingestion Architecture and A complex enterprise application uses different kinds of data, and Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann (Apache Samza). Designing Data-Intensive Applications: The Big Ideas Behind
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Big Data: Principles and best practices of scalable realtime data systems. Using logs to build a solid data infrastructure (or: why dual writes are
How does your database store data on disk reliably? Drawing from the experience of building scalable systems at LinkedIn and other startups, this talk explores why logs are such a fine idea: making it easier to maintain search Designing Data-Intensive Applications Big surprise: they use a log!

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