Accelerate versus Designing Data-Intensive Applications.
Both show up on every "best" list. They're not competitors. They're a sequence. Here's which one to read first, and when.
Reviewed by Ashish Sheth · Updated July 2026
Option B
Designing Data-Intensive Applications
Martin Kleppmann, Chris Riccomini · 2026
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Author
Nicole Forsgren, Jez Humble, Gene Kim
Martin Kleppmann, Chris Riccomini
Pages
288
720
Published
2018
2026
Publisher
IT Revolution Press
O'Reilly Media
Level
intermediate
intermediate to advanced
Amazon Rating
4.4/5 (3,400)
4.7/5 (312)
Goodreads Rating
4.05/5 (8,250)
4.55/5 (480)
Accelerate
Strengths
+ Rigorous research, not opinion, behind every claim
+ Short and focused compared with most DevOps books
+ The DORA metrics gave the industry a shared scorecard
+ Ammunition for engineers making the case to leadership
Caveats
− Roughly the first half reads like a methods defense
− Light on step-by-step implementation detail
− Some findings now feel like accepted common knowledge
Designing Data-Intensive Applications
Strengths
+ Best-in-class explanations of distributed systems fundamentals
+ Vendor-neutral: teaches principles, not specific tools
+ Excellent diagrams that make consensus and replication finally click
+ 2nd edition refreshes every chapter and adds AI/ML data systems coverage
Caveats
− Dense: not a weekend read, expect 3-4 months at one chapter per week
− Light on hands-on code; pair with a database internals book for implementation depth
− Some readers wish the new edition went deeper on cloud-native specifics
The verdict
Read Accelerate first to build foundations, then move to Designing Data-Intensive Applications for advanced concepts.
Accelerate
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Designing Data-Intensive Applications
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Frequently asked
Which is better, Accelerate or Designing Data-Intensive Applications?
Read Accelerate first to build foundations, then move to Designing Data-Intensive Applications for advanced concepts.
Is Accelerate still relevant in 2026?
Yes. The four DORA metrics it introduced are now an industry standard for measuring delivery, and the finding that speed and stability rise together still guides teams. It is short, evidence-based, and remains the reference for what actually improves performance.
Is the 2nd edition of Designing Data-Intensive Applications worth buying if I already own the first?
If you read the first edition cover to cover already, the upgrade is incremental: every chapter is refreshed and there's new coverage of AI/ML data systems, cloud-native architectures, and modern streaming. If you skimmed the first or read it years ago, the 2nd edition is the better starting point.