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Ebook About Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. 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.Peer under the hood of the systems you already use, and learn how to use and operate them more effectivelyMake informed decisions by identifying the strengths and weaknesses of different toolsNavigate the trade-offs around consistency, scalability, fault tolerance, and complexityUnderstand the distributed systems research upon which modern databases are builtPeek behind the scenes of major online services, and learn from their architecturesBook Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Review :
In Silicon Valley, "ability to code" is now the uber-metric to track. Starting from how engineers are interviewed, actual hands-on work (due to processes that overemphasizes "do" over "think, e.g., daily stand-ups require you to say what concrete thing you did yesterday), evaluation of work ("move fast and break things") to over-emphasizing on downstream "fixes" (prod-ops culture, 24*7 firefighting heroism) - the top echelon of technology gravitated towards things that it can see, feel, measure. What often gets neglected in this "code be all" culture is deep understanding of fundamental concepts, and how most newer "innovations" are indeed built on a handful time-honored principles.Nowhere else perhaps is this more prominent than in data space that up-levels libraries and frameworks as the conversation starter. That gets in the way of success. It is indeed impossible to model Cassandra "tables" without understanding - at least - quorum, compaction, log-merge data structure. Due to the way the present day solutions are built ("fits one use case perfectly well"), if these solutions are not implemented well to the particular domain, failure is just a release away.Mr Kleppmann does a great job of articulating the "systems" aspects of data engineering. He starts from a functional 4 lines code to build a database to the way how one can interpret and implement concurrency, serializability, isolation and linearizability (the latter for distributed systems). His book also has over 800 pointers to state of the art research as well as some of the computer science's classic papers. The book slows down its pace on the chapter on Distributed System and on the final one. A good editor could have trimmed about 120 pages and still retain most value one could get from the book.That said, if you ever worked on data systems, especially across paradigms (IMS -> RDBMS -> NoSQL -> Map-Reduce -> Spark -> Streaming -> Polyglot), this book is pretty much only resource out there to tie the "loose ends" and paint a coherent narrative. Highly recommended! I'm only 3 chapters into this book and I think it deserves a 5 star already.If you are interested in distributed systems or scalability, this book is a must-read for you. It gives you a high level understanding of different technology, including the idea behind it, the pros and cons, and the problem it is trying to solve. A great book for practitioners who want to learn all the essential concepts quickly.I didn't come from a traditional CS background, but I did have some basic knowledge in hardware and data structure. You will need some of that, such as hard disk vs SSD and AVL tree, to understand the materials. If you are completely new to backend or DS, you may want to start with another book "Web Scalability for Startup Engineers." After that book, you can read the free article "Distributed Systems for Fun and Profit" and you are good to go for this amazing book :D Read Online Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Download Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems PDF Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Mobi Free Reading Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Download Free Pdf Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems PDF Online Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Mobi Online Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Reading Online Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Read Online Martin Kleppmann Download Martin Kleppmann Martin Kleppmann PDF Martin Kleppmann Mobi Free Reading Martin Kleppmann Download Free Pdf Martin Kleppmann PDF Online Martin Kleppmann Mobi Online Martin Kleppmann Reading Online Martin KleppmannDownload Mobi Shikake: The Japanese Art of Shaping Behavior Through Design By Naohiro Matsumura
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