Well if you have used geohashes, have an idea of the all use cases, you would know the purpose. :)
One sample use case would be, if you want to find which polygon (building or administrative regions like states or cities) a given location falls into, doing a point in polygon for a huge set wouldn't be the best solution. Here comes the use of geohash and s2 cells. Using GeoRaptor on the initial set of geohashes reduces the search space considerably. For instance, the entire shape of the US creates 18 million geohashes which get reduced to ~220K when compressed.
One sample use case would be, if you want to find which polygon (building or administrative regions like states or cities) a given location falls into, doing a point in polygon for a huge set wouldn't be the best solution. Here comes the use of geohash and s2 cells. Using GeoRaptor on the initial set of geohashes reduces the search space considerably. For instance, the entire shape of the US creates 18 million geohashes which get reduced to ~220K when compressed.