Designing Data-Intensive Applications
Martin is a distributed systems researcher at the University of Cambridge. He previously worked as a software engineer and entrepreneur at firms such as LinkedIn and Rapportive, where he focused on large-scale data infrastructure.
Today, data is at the heart of many system design difficulties. Difficult challenges, such as scalability, consistency, dependability, efficiency, and maintainability, must be addressed. Furthermore, we have a dizzying array of technologies, such as relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the best options for your situation? How do you make sense of all this jargon?
Author Martin Kleppmann guides you through this broad terrain by evaluating the benefits and drawbacks of various data processing and storage systems. Although software evolves, the core principles remain constant. Designing Data-Intensive Applications will teach software developers and architects how to put those principles into practice and make full use of data in modern systems. Martin is also a frequent conference speaker, blogger, and contributor to open source.
- Examine the systems you already use and learn how to use and operate them more efficiently.
- Make informed decisions by evaluating the advantages and disadvantages of various tools.
- Determine the trade-offs between consistency, scalability, fault tolerance, and complexity.
- Recognize the distributed systems research on which modern databases are based.
- Investigate the architectures of key internet services and learn from them.
Author: Martin Kleppmann
Link to buy: https://www.amazon.com/Designing-Data-Intensive-Applications-Reliable-Maintainable/dp/1449373321/
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