  This work aims at analyzing how two different concurrency models, namely the
shared memory model and the actor model, can influence the development of
applications that manage huge masses of data, distinctive of Big Data
applications. The paper compares the two models by analyzing a couple of
concrete projects based on the MapReduce and Bulk Synchronous Parallel
algorithmic schemes. Both projects are doubly implemented on two concrete
platforms: Akka Cluster and Managed X10. The result is both a conceptual
comparison of models in the Big Data Analytics scenario, and an experimental
analysis based on concrete executions on a cluster platform.
