Engineering a High-Performance LSM-Tree Storage Engine: MemTables, SSTables, and Compaction

Short summary

LSM-Trees optimize write-heavy databases by converting random disk writes into sequential appends, enabling high throughput in RocksDB, Cassandra, and InfluxDB. Data flows through a Write-Ahead Log, in-memory MemTable, and Sorted String Tables with Bloom Filters and sparse indices for fast lookups. Leveled compaction merges SSTables across levels to manage space and read amplification.

• •LSM-Trees use sequential disk appends instead of random I/O, powering modern high-performance databases
• •Data architecture: Write-Ahead Log → MemTable → SSTables with Bloom Filters and sparse indices for efficient lookups
• •Leveled compaction merges SSTables to reduce space waste and read overhead

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