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Fundamentals of Environmental and Toxicological Chemistry: Sustainable Scien…

Posted July 14, 2026 by & filed under .

Condition Notes: A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear.

Brogdon’s Forensic Radiology by Michael J Thali M D: Used

Posted July 14, 2026 by & filed under .

Like new condition

United Nations Statistical Yearbook 58th Issue 2013 Hardcover

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The product is the “2013 United Nations Statistical Yearbook 58th Issue” published in 2016 by United Nations Publications. It is a textbook on Mathematics and Political Science, focusing on Probability & Statistics and International Relations. The hardcover book is a part of the United Nations Statistical Yearbook series, with 614 pages in English, measuring 11.1 inches in length, 8.5 inches in width, and 1.5 inches in height, weighing 59.3 ounces. This book is a former library copy and has library stamps in various locations, see photos.

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

Posted July 14, 2026 by & filed under .

You will find that this textbook uses real data sets for exercises.

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

Posted July 14, 2026 by & filed under .

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…

Posted July 14, 2026 by & filed under .

“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.

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

Posted July 14, 2026 by & filed under .

“Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems” by Martin Kleppmann is a textbook published by O’Reilly Media in 2017. This trade paperback book covers the subject of data modeling and design for desktop applications and databases. With 614 pages, it provides in-depth insights on creating efficient and robust data-intensive applications. Written in English, this book is a valuable resource for those interested in understanding the fundamental principles behind dependable and scalable systems.

DESIGNING DATA-INTENSIVE APPLICATIONS: THE BIG IDEAS BEHIND REL… Martin Kleppm

Posted July 14, 2026 by & filed under .

Please Note: All photos in our listings are stock photos unless stated differently. This item will ship internationally, please take note of the shipping time displayed by eBay. If you are located in the US or UK, international orders will be forwarded to our warehouse in your country before final delivery to you, and tracking will not start updating until your order has reached your country. Thank you for supporting my family business.

Designing Data-Intensive Applicatio…, Martin Kleppman

Posted July 14, 2026 by & filed under .

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,…

Posted July 14, 2026 by & filed under .

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Kleppmann, Martin May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less

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