Tech
Designing Data-Intensive Applications
by Martin Kleppmann
The definitive guide to the big ideas behind reliable, scalable, and maintainable data systems. Covers everything from database internals to distributed consensus, stream processing, and the future of data.
distributed-systemsdatabasesarchitecturedata-engineering
Chapters (4)
1
Foundations of Data Systems
Reliability, scalability, and maintainability — the three pillars of good data system design.
💡 3 insights📝 4 notes💬 2 quotes
2
Data Models and Storage
How data is stored and queried — from relational models to document stores, LSM-trees, and B-trees.
💡 3 insights📝 4 notes💬 2 quotes
3
Distributed Data
Replication, partitioning, and the fundamental challenges of distributing data across multiple machines.
💡 3 insights📝 4 notes💬 2 quotes
4
Derived Data and Stream Processing
Batch processing, stream processing, and how to build reliable data pipelines.
💡 3 insights📝 4 notes💬 2 quotes