NoSQL

Before MongoDB, Redis, Cassandra, or Neo4j make any sense as separate books, you need the one idea that explains why NoSQL exists at all, and the one theorem that explains why every NoSQL database behaves differently under stress.

The two knobs every distributed database turns, underneath whatever query language it presents to you: how it copies data (replication) and how it splits data across machines (partitioning). MongoDB, Cassandra, and Neo4j clustering all reduce to variations on these two ideas.

Caching and CQRS are the two system-design tools you reach for once a single database, however well-indexed, can't serve your read pattern fast enough or shaped correctly enough. Both show up constantly in system-design interviews, and both are easy to reach for too early.

A cluster can be perfectly modeled, perfectly indexed, and pass every load test — and still cause a real outage or breach for reasons that have nothing to do with schema design. This chapter is the operational layer every family-specific book after this one assumes you already understand.