From dict to DashTable: How Dragonfly cuts memory overhead by 40%

Dragonfly replaces Redis’s traditional dictionary implementation with DashTable, an extendible-hashing structure designed to reduce memory overhead and avoid whole-table rehashing. Redis grows by allocating a second, larger hash table and incrementally migrating entries, which spreads latency costs but creates temporary memory spikes and requires lookups across both tables during rehashing. DashTable instead organizes entries into fixed-size segments addressed through a directory; when insertion capacity is exhausted, it splits only the affected segment and redistributes at most 840 entries, while directory expansion moves pointers rather than key-value data. Its insertion process also attempts nearby buckets, entry displacement, stash buckets, and expired-key cleanup before splitting. The post estimates DashTable’s steady-state storage at about 18.6 bytes per entry, compared with Redis’s estimated 32–48 bytes including bucket overhead and rehash effects, and reports a benchmark in which Dragonfly used roughly 4.3 GB for 100 million keys versus Redis’s 7.5 GB, a reduction of about 43%. It also notes that Redis 7.x mitigates large rehash events through multiple internal dictionaries, whereas DashTable addresses the issue through localized segment-level growth.

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