  Interactive data-intensive applications are becoming ever more pervasive in
domains such as finance, web applications, mobile computing, and Internet of
Things. Increasingly, these applications are being deployed in sophisticated
parallel and distributed hardware infrastructures. With this growing diversity
of the software and hardware landscape, there is a pressure on programming
models and systems to enable developers to design modular, scalable, efficient,
and consistent data-intensive applications. In response to this challenge,
recent research has advocated the integration of actor programming models and
database management. This integration promises to help developers build
logically distributed micro-applications well adapted to modern hardware trends
as opposed to existing approaches targeted at optimizing monolithic
applications.
  Towards this aim, in this paper we analyze, make the case for, and present a
broad vision of actor-relational database systems. We argue why the time is
ripe today to examine the research opportunities afforded by this emerging
system paradigm. Based on this discussion, we present design principles as well
as candidate feature sets to help concretize the vision for such systems. To
illustrate the usefulness of the proposed feature set and motivate the need for
this class of systems, we show a detailed case study inspired by a smart
supermarket application with self-checkout, along with evidence for performance
benefits on modern hardware.
