The requirements for OLTP database systems are becoming ever
more demanding. Domains such as finance and computer games
increasingly mandate that developers be able to encode complex
application logic and control transaction latencies in in-memory
databases. At the same time, infrastructure engineers in these domains
need to experiment with and deploy OLTP database architectures
that ensure application scalability and maximize resource utilization
in modern machines. In this paper, we propose a relational
actor programming model for in-memory databases as a novel,
holistic approach towards fulfilling these challenging requirements.
Conceptually, relational actors, or reactors for short, are applicationdefined,
isolated logical actors that encapsulate relations and process
function calls asynchronously. Reactors ease reasoning about
correctness by guaranteeing serializability of application-level function
calls. In contrast to classic transactional models, however, reactors
allow developers to take advantage of intra-transaction parallelism
and state encapsulation in their applications to reduce latency
and improve locality. Moreover, reactors enable a new degree of
flexibility in database deployment. We present ReactDB, a system
design exposing reactors that allows for flexible virtualization of
database architecture between the extremes of shared-nothing and
shared-everything without changes to application code. Our experiments
illustrate latency control, low overhead, and asynchronicity
trade-offs with ReactDB in OLTP benchmarks