Both tall and distributed arrays are designed for processing large amounts of data, but they have somewhat different capabilities.
distributed arrays exist spread across the memory of several MATLAB worker processes - so the largest distributed array you can create is limited by the total amount of physical memory you have. Also, distributed arrays are more oriented towards dense and sparse linear algebra. distributed arrays require Parallel Computing Toolbox, and are most effective when used with MATLAB Distributed Computing Server (which allows the use of multiple machines across which to distribute the data).
The data for tall arrays exists on disk, and so their size is not limited by the amount of memory you have available. However, as the name implies, tall arrays can be large only in the first dimension. tall arrays are more geared towards data analytics. tall arrays ship with MATLAB itself, but there is enhanced support in both Parallel Computing Toolbox (which enables parallel processing in a single computer) and MATLAB Distributed Computing Server (which enables parallel processing across a cluster, including Hadoop/Spark clusters).
