It is well documented that fast writing into an entity kind with monotonically increasing values as key or indexed properties is a bad idea for performance.
How about indexing the entities on boolean properties or properties with enum-like values such as Genders?
My guess is indexing on a low-cardinality property will probably suffer from the same problem, because there is no built-in type for such properties. But maybe there is special treatment for boolean properties?
Cloud Datastore has optimizations in place for low-cardinality data such as booleans and enums. Each index entry also contains the entity key, which can then allow our underlying Bigtable tablets to efficiently split and hence handle larger load. This works since we don't need to consider sort order for the same value, so having them randomly distributed within their own key space makes no difference to queries, and the entity key is guaranteed to be unique so we avoid collisions.
When we index a value we also add a 'scatter key' property to the end, which is essentially a randomized integer. This scatter key can then be used for query splitting later, allowing things like Cloud Dataflow to efficiently parallelize queries against this dataset.