Data at scale
An interactive guide to distributed data systems, from one table and one disk to a full data platform.
Finished
A first-principles explainer of Hadoop, Spark, column stores, Redshift, Cassandra and lakehouses, built around the problems they solve.
Step through MapReduce, file replication, Spark recovery, Cassandra’s hash ring and transaction logs. Adjust the calculators to explore scan times, caching, column-store reads and quorum trade-offs, or follow one parcel scan through a complete data platform.
The chapters, diagrams, glossary and check questions remain readable without JavaScript. JavaScript adds step-by-step playback, calculators, diagram toggles and glossary filtering. With reduced motion enabled, diagrams can still be stepped through manually.