H3: For indexing geographies into a hexagonal grid, by Uber

I've read all the comments here and still don't understand the rationale for hexagons as opposed to squares. In every sense, squares seem to be much easier to reason about and easier to hierarchically partition than hexagons are. There are certain advantages to hexagons in certain contexts, like six degrees of movement instead of four in board games, but I don't see how any of those advantages translate here for geographical indexing. I'd love to understand why hexagons as opposed…

S2 is used pretty heavily across the industry. Comparison - (https://h3geo.org/docs/comparisons/s2/) H3 doesn't guarantee a child hexagon at level N+1 strictly belongs to 1 parent at level N. S2 is built on this exactly this primitive, but then struggles with cell-size variability across latitude. This lack of strict hierarchy seeming negates alot of practical benefits (e.g tree data-structure that maps well to sharding and aggregation). Whilst I haven't dug into H3 that much from a practical sense - but I…