LSM trees create SSTables fast but need compaction. Learn size-tiered vs leveled compaction strategies and the write vs read amplification tradeoff.

LSM Trees vs B-Trees: the write-fast or read-fast tradeoff. Learn when to use B-trees (MySQL) vs LSM trees (Cassandra) based on your database workload.

How do databases survive crashes and ensure durability? Learn how Write-Ahead Logging (WAL) uses sequential writes to guarantee data persistence without killing performance.

How do stale replicas catch up in distributed systems? Compare read repair and anti-entropy strategies with Merkle trees for healing data divergence.

Concurrent writes in distributed databases don’t merge automatically. Learn to detect conflicts with version vectors and resolve them without losing data.

Users see stale data after writes. It’s not a bug, it’s replication lag. Learn to handle read-after-write problems and causality violations in production.

Eventual consistency doesn’t mean milliseconds. Understand linearizability, causal consistency, and quorum reads to pick the right consistency model.

Querying partitioned databases by non-partition keys? Learn the tradeoffs between local and global secondary indexes in distributed systems.

Every JOIN multiplies query complexity. Learn the three JOIN strategies databases use and when denormalization beats JOIN performance by 30x.

More indexes don’t mean faster queries. Learn when to add, remove, and optimize database indexes. Real examples of 7x performance gains through strategic indexing.

Understand virtual nodes in consistent hashing through a simple three-layer model that decouples data distribution from server topology in distributed systems.

Stop guessing at performance problems. Learn the 5-step systematic framework for debugging slow queries that helped reduce query times from 2+ seconds to 30ms.