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Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable,
Used – Very Good
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable,
Used – Very Good
Designing Data-Intensive Applications The Big Ideas Behind Reliable…
Donated item. Average wear from use. Book is in good condition. Spine and cover intact. Pages clean and tight. Cover shows dents and wear.
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable,
The book is in good condition. Include some spoils, bent corners.
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable,
The book is in good condition. Include some spoils, bent corners.
Designing Data-Intensive Applications : The Big Ideas Behind Reliable, Scalable,
You will find that this textbook uses real data sets for exercises.
Designing Data-Intensive Applications: the Big Ideas behind Reliable, Scalable,
What are the right choices for your application?. How do you make sense of all these buzzwords?. 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: The Big Ideas Behind Reliable, Scalable..
Notes: Stain on bottom edge and wrinkled pages. Sugarhouse Book Works, LLC presents. Qty Available: 1.
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalab…
“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.