  We introduce the concept of design continuums for the data layout of
key-value stores. A design continuum unifies major distinct data structure
designs under the same model. The critical insight and potential long-term
impact is that such unifying models 1) render what we consider up to now as
fundamentally different data structures to be seen as views of the very same
overall design space, and 2) allow seeing new data structure designs with
performance properties that are not feasible by existing designs. The core
intuition behind the construction of design continuums is that all data
structures arise from the very same set of fundamental design principles, i.e.,
a small set of data layout design concepts out of which we can synthesize any
design that exists in the literature as well as new ones. We show how to
construct, evaluate, and expand, design continuums and we also present the
first continuum that unifies major data structure designs, i.e., B+tree,
B-epsilon-tree, LSM-tree, and LSH-table.
  The practical benefit of a design continuum is that it creates a fast
inference engine for the design of data structures. For example, we can predict
near instantly how a specific design change in the underlying storage of a data
system would affect performance, or reversely what would be the optimal data
structure (from a given set of designs) given workload characteristics and a
memory budget. In turn, these properties allow us to envision a new class of
self-designing key-value stores with a substantially improved ability to adapt
to workload and hardware changes by transitioning between drastically different
data structure designs to assume a diverse set of performance properties at
will.
