http://ddinsights.net/tags/storage/Recent content in Storage on Distributed Data InsightsHugoen-usTue, 02 Jun 2026 08:30:00 -0700http://ddinsights.net/posts/lsm-trees-vs-btrees/Tue, 02 Jun 2026 08:30:00 -0700http://ddinsights.net/posts/lsm-trees-vs-btrees/<p>Underneath nearly every database is one of two storage engines: a <strong>B-tree</strong> or an <strong>LSM-tree</strong>. The choice shapes write throughput, read latency, space usage, and how the system behaves under pressure. It&rsquo;s worth understanding <em>why</em> the big distributed stores — Cassandra, RocksDB, HBase, ScyllaDB — overwhelmingly chose LSM-trees.</p> <h2 id="b-trees-update-in-place">B-trees: update in place</h2> <p>A B-tree keeps data sorted in fixed-size pages and <strong>mutates pages in place</strong>. To update a key, you find its page and overwrite it. Reads are excellent — typically a handful of page lookups — and the structure has powered relational databases for decades.</p>