I'm confused about the advantage of embedded key-value databases over the naive solution of just storing one file on disk per key. For example, databases like RocksDB, Badger, SQLite use fancy data structures like B+ trees and LSMs but seem to get roughly the same performance as this simple solution.
For example, Badger (which is the fastest Go embedded db) takes about 800 microseconds to write an entry. In comparison, creating a new file from scratch and writing some data to it takes 150 mics with no optimization.
EDIT: to clarify, here's the simple implementation of a key-value store I'm comparing with the state of the art embedded dbs. Just hash each key to a string filename, and store the associated value as a byte array at that filename. Reads and writes are ~150 mics each, which is faster than Badger for single operations and comparable for batched operations. Furthermore, the disk space is minimal, since we don't store any extra structure besides the actual values.
I must be missing something here, because the solutions people actually use are super fancy and optimized using things like bloom filters and B+ trees.