Cache engines are used as an intermediate store for computed report data. Since pulling and processing the data for a report can be computationally intensive, this cached storage allows us to sort and page through the resulting report very quickly and easily.
Currently, the easiest to get up and running is Filesystem caching, as it has no dependencies outside of Python and simply caches to the local filesystem. However, it cannot handle concurrent connections and is generally a poor choice outside of the development environment. At the moment, the preferred choice for deployment is Redis caching.