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Storage Systems: Databases, Caches, and Data Structures
System & ML-System Design

Storage Layer: Database Selection, KV Stores, and LSM Trees

TechnicalMedium~30 minDesigned by experts

About this interview

A technical interview on Storage Systems: Databases, Caches, and Data Structures, pitched at the medium level. A voice AI interviewer leads the conversation, adapts its questions to your answers, keeps you on topic, and afterward gives you honest, specific feedback on where you were strong and where to improve. Expect roughly 30 minutes.

What you'll be assessed on

Compare relational, columnar, document, graph, and key-value stores and select the right type for a use case
Explain KV store internals: SSTables, LSM trees, Bloom filters, and compaction
Describe B-tree and B+ tree indexes: how they differ and when each is preferable
Explain write-amplification, read-amplification, and space-amplification tradeoffs in storage engines

Topics covered

Database SelectionStorage Engine TradeoffsB-Trees and B+ TreesKV Store Internals / LSM TreesDistributed KV Store Design

A few sample questions

Just examples to set expectations - the real interview has many more and adapts to your responses.

When an interviewer asks you to pick a database for a feature, what are the first three questions you should ask to narrow down the choice?
Why do B+ tree leaf nodes being linked together matter in practice for a database workload?
Your distributed KV store is configured with N=3, W=1, R=1. What are the availability and consistency characteristics of this configuration, and what kind of workload is it suited for?

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