In LSM tree-based storage engines like RocksDB, a single 1MB write can result in approximately 30MB of data being written to disk (8x amplification) because data is written to memory first, then dumped as sorted files (SSTables) when buffers fill, and each level transition requires rewriting all existing data in that level; the choice between size-tiered compaction (fewer levels, lower write amplification, slower reads) and leveled compaction (more levels, faster reads, higher write amplification) depends on whether the workload is write-heavy or read-heavy.
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Deep Dive
Your 1MB write hits disk as 30MB on a healthy RocksDB instanceAdded:
Your 1 MB write hits disk as 30 MB, same [music] data written eight times over.
Writes land in memory first. When that buffer fills, it dumps to disk as a sorted file. So far, one write equals one write. Data lives in levels. Each one is 10 times bigger than the level above. When a level fills, the engine merges it into the next one down, rewriting every byte already there. Four levels deep, that's eight times the write you asked for.
>> [music] >> Here's the catch. Fewer levels, less rewriting, but slower lookups. More levels, faster queries, but bigger write amp. So, pick the compaction strategy that fits your workload. Write [music] heavy logs go size tiered, like Cassandra. Read heavy lookups go leveled, like RocksDB. Your storage engine choice is your write amp curve.
Same bytes eight times over. Pick the strategy, not the database.
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