So I was eager to know like these AI/ML specific work needs to store something in the persistent kv database? like for example do they needs to use LMDB for any work? Lets say if I have to design a persistent kv database in 2026 for AL/ML workload what should I keep in mind ? and at the first place do they even need ?
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So as we know, databases like DragonflyDB can persist data on disk and also use modern async IO techniques like io_uring.
Then why would someone choose a persistent key-value database/storage engine like FoundationDB, TiKV, ScyllaDB, or LMDB-style systems instead?
What architectural or workload differences make those systems preferable over something like DragonflyDB with persistence enabled?
Trying to understand the deeper storage-engine tradeoffs here.
**NOT WRITTEN BY AI** excepts some comments(because of language barrier) and small utilities. 98% of the code is written by me :