Apache Cassandra
maang.io System Design Series
Apache Cassandra is a masterless, wide-column database built for enormous write volume and always-on availability. It marries Dynamo's distribution (a consistent-hashing ring, leaderless replication, tunable consistency) to Bigtable's storage (the LSM-tree engine). No single point of failure, linear scale by adding nodes, and a consistency dial you turn per query — it's the self-managed cousin of DynamoDB and a system-design interview staple.
This deep dive comes in four parts:
- Foundations & Core Concepts — the masterless ring, partition keys, and replication factor.
- Internals — the write path (commit log → memtable → SSTable) and the LSM storage engine, with worked numbers.
- Advanced Internals — the read path, tunable consistency (
R + W > RF), repair, and tombstones. - Interview — Staff/Principal Q&A: data modeling, consistency reasoning, and failure handling.
Apache Cassandra — Part 4: System Design & Interview Mastery
maang.io System Design Series
What is this?
You now know Cassandra from the ring down to the SSTable. This chapter is where that knowledge earns you the offer. An interviewer doesn't want you to recite "Cassandra uses an LSM-tree" — they want to watch you reach for it at the right moment, model data correctly, and defend the trade-offs when they push back. That's the difference between a senior signal and a memorized fact.
We'll do two things: first see where Cassandra fits in real designs (with a full data model), then run a mock interview — for each question, what they're really asking, a model answer, and the senior line that signals you've done this for real.
The one-line idea: interviewers use Cassandra to test whether you can match a datastore's shape to a workload's shape — high-write, key-accessed, always-on — and then live honestly with the costs (no joins, no ad-hoc queries, eventual consistency unless you pay for it).
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