  Traditionally, DBMSs separate their storage layer from their indexing layer.
While the storage layer physically materializes the database and provides
low-level access methods to it, the indexing layer on top enables a faster
locating of searched-for entries. While this clearly separates concerns, it
also adds a level of indirection to the already complex execution path. In this
work, we propose an alternative design: Instead of conservatively separating
both layers, we naturally fuse them by integrating an adaptive coarse-granular
indexing scheme directly into the storage layer. We do so by utilizing tools of
the virtual memory management subsystem provided by the OS: On the lowest
level, we materialize the database content in form of physical main memory. On
top of that, we allow the creation of arbitrarily many virtual memory storage
views that map to subsets of the database having certain properties of
interest. This creation happens fully adaptively as a side-product of query
processing. To speed up query answering, we route each query automatically to
the most fitting virtual view(s). By this, we naturally index the storage layer
in its core and gradually improve the provided scan performance.
