One thing I'd add about GeoMesa's use of space-filling curves is that most of the databases used are key-value stores. Given that, it is somewhat unwieldy to m

One thing I'd add about GeoMesa's use of space-filling curves is that most of the databases used are key-value stores. Given that, it is somewhat unwieldy to manage R-tree indexes. Also, GeoMesa implements an 'XZ'-curve schema which gets around a few of the problems just using a Z-order curve runs into. To the point about hot-spotting, there's a configurable sharding strategy that can help spread the data around more of the nodes in the cluster. I haven't seen an easy/obvious way to apply adaptive quad-tries on top of key-value stores like Accumulo and HBase. Managing complex data structures in a cloud seems to be rather difficult.