What You'll Learn
Master PostgreSQL internals: MVCC, WAL, query planner
Design multi-region database replication strategies
Understand CAP theorem, PACELC, and consistency models
Build high-throughput Redis caching architectures
Implement distributed transactions with 2PC and Sagas
Design time-series & columnar storage for analytics at scale
Achieve 99.999% uptime with chaos engineering practices
Migrate production databases with zero downtime
Course Description
Databases are the most unforgiving layer in any stack. A wrong schema decision made today will haunt your team for years. This course teaches you to get it right from the start — and fix it when it's already wrong.
Kai Larsen spent 8 years at MongoDB working on the distributed query engine that powers millions of production databases. He's seen every failure mode, every corrosion pattern, every disaster caused by misunderstanding consistency guarantees in a distributed system.
This is not a SQL tutorial. This is a course for engineers who already know databases and want to understand them at the systems level — the internals, the trade-offs, and the architectural decisions that determine whether your data layer survives scale.
Prerequisites
Curriculum Overview
36 modules · 58hHow Databases Actually Work
5 lessons · 4h 00m
Distributed Systems & CAP Theorem
6 lessons · 5h 30m
34 more modules — Redis Architecture, NoSQL Design, Chaos Engineering, Zero-Downtime Migration...
Your Instructor
22,800 students
3 courses
Kai Larsen
Distributed Systems Lead · Ex-MongoDB · IEEE Member
Kai spent 8 years at MongoDB working on the distributed query engine that now powers over 46,000 customers. He holds 3 patents in distributed database replication and has been an IEEE senior member since 2019. He now consults for companies managing petabyte-scale data infrastructure and teaches this course as his way of giving back to the engineering community.
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