  This paper discusses a novel data structure that efficiently implements label
based graph queries particularly for very large graphs. The major issues in
large graph databases is the memory foot-print of label based property
associations to graph entities and subsequent query speeds. To this end, unlike
the available graph databases, that use key-value pairs using map like
associative containers, we have devised a novel data structure that is superior
in its memory foot-print as well as its fast search characteristics without any
compromise on the number of labels that can be associated to graph nodes and
edges. We will demonstrate the power of this novel unconventional data
structure over billion plus graphs within the context.
