This paper presents a Haskell library for graph processing:
DeltaGraph. One unique feature of this system is that intentions
to perform graph updates can be memoized \emph{in-graph} in a
decentralized fashion, and the propagation of these intentions
within the graph can be decoupled from the realization of the
updates. As a result, DeltaGraph can respond to updates in
constant time and work elegantly with parallelism support. We
build a Twitter-like application on top of DeltaGraph to
demonstrate its effectiveness and explore parallelism and
opportunistic computing optimizations.