  This paper introduces H-STREAM, a big stream/data processing pipelines
evaluation engine that proposes stream processing operators as micro-services
to support the analysis and visualisation of Big Data streams stemming from IoT
(Internet of Things) environments. H-STREAM micro-services combine stream
processing and data storage techniques tuned depending on the number of things
producing streams, the pace at which they produce them, and the physical
computing resources available for processing them online and delivering them to
consumers. H-STREAM delivers stream processing and visualisation micro-services
installed in a cloud environment. Micro-services can be composed for
implementing specific stream aggregation analysis pipelines as queries. The
paper presents an experimental validation using Microsoft Azure as a deployment
environment for testing the capacity of H-STREAM for dealing with velocity and
volume challenges in an (i) a neuroscience experiment and (in) a social
connectivity analysis scenario running on IoT farms.
