# Spatial Indexes

Hierarchical grid systems such as Quadbin are an essential tool for analysing large spatial datasets, especially when dealing with data sources in different spatial aggregations. These systems are based on geospatial indexes that provide a direct relationship between grid cells at different resolutions, enabling extremely performant spatial operations.

<table data-view="cards"><thead><tr><th></th><th></th><th></th><th data-hidden data-card-cover data-type="files"></th></tr></thead><tbody><tr><td>Quadbin (<a href="https://docs.microsoft.com/en-us/bingmaps/articles/bing-maps-tile-system">source</a>)</td><td></td><td></td><td><a href="/files/oz3crRb9Q96YEaF0WYxb">/files/oz3crRb9Q96YEaF0WYxb</a></td></tr></tbody></table>

Go to the [Reference](https://docs.carto.com/data-and-analysis/analytics-toolbox-for-databricks/reference/quadbin) for the full list of available functions. If you can’t find what you need, please let us know by opening an issue in our [Github repository](https://github.com/CartoDB/carto-spatial-extension) or become a contributor.

## Quadbin <a href="#quadbin" id="quadbin"></a>

Quadbin is a hierarchical geospatial index based on the [Bing Maps Tile System](https://docs.microsoft.com/en-us/bingmaps/articles/bing-maps-tile-system) (Quadkey). Designed to be cluster-efficient, it stores in a 64-bit number the information to uniquely identify any of the grid cells that result from uniformly subdividing a map in Mercator projection into four squares at different resolution levels, from 0 to 26 (less than 1m² at the equator). The bit layout is inspired in the H3 design, and provides different modes to store not only cells, but edges, corners or vertices.


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