The "document" is sort of the native data type, Put everything in a big hierarchical structure, It is very flexible but analytics across the set can suffer. "relational" is another way to store data, break your big hierarchy into sets of related rows and store the rows as a table, If I were to describe it in geometric terms where the document is a report on a paper, the relation is a vertical slice through a stack of those reports. This is slightly non-intuitive but provides for interesting analysis opportunities.

But nothing prevents you from treating your relational database as a document database, set it up as a key-value store where each key is is the document title and each value is a large blob of document data. If your documents are fairly consistent it is also easy enough to build indexes and query features to regain some of the analytical ability of relational data.