For what it's worth, 10MB of JSON is not much. Duplicating the example entry from the article 63000 times (replacing `key` by a uuid4 for unicity) yields 11.5MB JSON.
Deserialising that JSON then inserting each entry in a dict (indexed by key) takes 450ms in Python.
But as Bruce Dawson oft notes, quadratic behaviour is the sweet spot because it's "fast enough to go into production, and slow enough to fall over once it gets there". Here odds are there were only dozens or hundreds of items during dev so nobody noticed it would become slow as balls beyond a few thousand items.
Plus load times are usually the one thing you start ignoring early on, just start the session, go take a coffee or a piss, and by the time you're back it's loaded. Especially after QA has notified of slow load times half a dozen times, the devs (with fast machines and possibly smaller development dataset) go "works fine", and QA just gives up.