Inability to scale with sustained usage (1+ person*year of data) is the fatal problem with this category in existing approaches. Root of this is primarily the “partial sync problem” - when dataset outgrows both the memory and compute resources available in the client device (which is unreliable, not under your control to make reliable, and resource constrained - and not everybody has the latest giga device), you have to somehow decide which working set to replicate. If the app structure is a graph and involves relational queries, this is undecidable without actually running the queries! If the app structure is constrained to topic documents, you still have to choose which topics to cache and it still falls over at document sizes easily seen in prolonged solo use let alone use at an enterprise which market is necessary to justify VC investment. All this in an increasingly connected world where the cloud is 10ms away from city/enterprise users (the $$$) and any offline periods (subway etc) resolve quickly, so a degraded offline mode (letting you edit whatever you were last looking at w/o global relational query etc) is often acceptable. Oh, and does your app need AI?
Change my view!