Data Unification with H3

Thanks to the H3 indexing, it is easy to build queries on top of the database. Using either H3 cells or coordinate pairs, you can retrieve the population based on a point, a given radius, or polygon. That way, it is straightforward to aggregate the population on a zip code level, for example.

We aggregate the squares into H3 cells at resolution 11 and store them in a MongoDB with the aggregated values for each demographic group. Using JS streams and MongoDB's aggregation pipelines, the memory usage stays low, and you can process millions of rows on your local machine.