Rethinking Kleppmann's “Designing Data-Intensive Applications”
How Martin Kleppmann’s iconic book evolved for AI and cloud-native architectures
Since its release in 2017, Designing Data-Intensive Applications (DDIA) has become known as the bible for anyone working on large-scale, data-driven systems. The book’s focus on fundamentals (like storage engines, replication, and partitioning) has helped it age well. Still, the world of distributed systems has evolved substantially in the past decade.
Cloud-native architectures are now the default. Object storage has become a first-class building block. Databases increasingly run everywhere from embedded and edge deployments to fully managed cloud services. And AI-driven workloads have made a mark on storage formats, query engines, and indexing strategies.
So, after years of requests for a second edition, Martin Kleppmann revisited the book – and he enlisted his longtime collaborator Chris Riccomini as a co-author. Their goal: Keep the core intact while weaving in new ideas and refreshing the details throughout. With the second...
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