Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalab…

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"Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems" by Martin Kleppmann is a comprehensive textbook published by O'Reilly Media in 2017. The book covers data modeling and design, desktop applications, and databases, making it a valuable resource for students and professionals in the computer science field. With 614 pages of content, this trade paperback book delves into the big ideas behind creating dependable, expandable, and manageable data-intensive applications, offering valuable insights for anyone looking to enhance their understanding of this subject area.

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

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The book covers data modeling and design, as well as desktop applications/databases, making it a valuable resource for those interested in computer-related subjects. With 614 pages, this trade paperback is written in English and provides insights on creating dependable and scalable systems for data-intensive applications.

Continuar lendoDesigning Data-Intensive Applications : The Big Ideas Behind Reliable, Scalable,

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

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"Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems" by Martin Kleppmann is a comprehensive textbook that covers the subject of data modeling and design for desktop applications and databases. Published by O'Reilly Media in 2017, this paperback book has 614 pages and is written in English. The book explores the concepts of reliability, scalability, and maintainability in the design of data-intensive applications, making it a valuable resource for computer science and technology students, as well as professionals in the field. With detailed insights and practical advice, this book provides a solid foundation for building robust and efficient systems.

Continuar lendoDesigning Data-Intensive Applications : The Big Ideas Behind Reliable, Scalable,