I did read the article before posting. They don’t actually explain why they opted to not use an R-tree except to say that they think this organizational structure makes sense intuitively. Unfortunately, intuition here is wrong, and the link I posted specifically benchmarks their solution and shows that if they had done even basic benchmarking they would have seen this.

Now there might be a valid argument for this approach if the geofences are changing constantly and reindexing the R-trees would take too long, but in the end they synchronize everything anyways, and the R-tree could easily be generated on another node, serialized and then unserialized asynchronously before swapping to an updated tree.