Cassandra

The single habit that makes or breaks a Cassandra schema: you design tables around the queries you'll run, not the entities you'd normalize in SQL. Get this one idea wrong and every later chapter is fighting the data model.

Cassandra's signature feature isn't that it replicates data — every distributed database does that. It's that you choose, on every single query, exactly how many replicas must agree before you trust the answer.

Cassandra is famous for extremely fast writes, for a specific, learnable reason. What matters for a developer isn't the file format underneath — it's that the speed is borrowed from reads and paid back by a background process you have to choose a strategy for.

CQL reads like SQL, which is exactly what makes its restrictions surprising the first time you hit one. This chapter covers what CQL will and won't let you query, and the two ways to add a second query pattern to an existing table — one of them a trap.

Every idea from the first four chapters — partition vs. clustering key, tunable consistency, query-first tables — shows up again here as annotations and method calls. This chapter is where they become code you'd actually ship.