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

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Data is at the center of many challenges in system design today. Difficult issues such as scalability, consistency, reliability, efficiency, and maintainability need to be resolved. In addition, there's an overwhelming variety of systems, including relational databases, NoSQL datastores, data warehouses, and data lakes. There are cloud services, on-premises services, and embedded databases. What are the right choices for your application? How do you make sense of all these buzzwords?

In this second edition, authors Martin Kleppmann and Chris Riccomini build on the foundation laid in the acclaimed first edition, integrating new technologies and emerging trends. You'll be guided through the maze of decisions and trade-offs involved in building a modern data system, learn how to choose the right tools for your needs, and understand the fundamentals of distributed systems.

Peer under the hood of the systems you already use, and learn to use them more effectively
Make informed decisions by identifying the strengths and weaknesses of different tools
Learn how major cloud services are designed for scalability, fault tolerance, and consistency
Understand the core principles upon which modern databases are built

Martin Kleppmann is a researcher in distributed systems and security at the University of Cambridge, and author of Designing Data-Intensive Applications (O'Reilly Media, 2017). Previously he was a software engineer and entrepreneur at Internet companies including LinkedIn and Rapportive, where he worked on large-scale data infrastructure. He is now working on TRVE DATA, a project that aims to bring end-to-end encryption and decentralisation to a wide range of applications.