  The "solar-stellar connection" began as a relatively small field of research
focused on understanding the processes that generate magnetic field in stars
and which sometimes lead to a cyclic pattern of long-term variability in
activity, as demonstrated by our Sun. This area of study has recently become
more broadly pertinent to questions of exoplanet habitability and exo-space
weather, as well as stellar evolution. In contrast to other areas of stellar
research, individual stars in the solar-stellar connection often have a
distinct identity and character in the literature, due primarily to the rarity
of the decades-long time series that are necessary for studying stellar
activity cycles. Furthermore, the underlying stellar dynamo is not well
understood theoretically, and is thought to be sensitive to several stellar
properties, e.g. luminosity, differential rotation, and depth of the convection
zone, which in turn are often parameterized by other more readily available
properties. Relevant observations are scattered throughout the literature and
existing stellar databases, and consolidating information for new studies is a
tedious and laborious exercise. To accelerate research in this area I developed
sunstardb, a relational database of stellar properties and magnetic activity
proxy time series keyed by individual named stars. The organization of the data
eliminates the need for problematic catalog cross matching operations inherent
when building an analysis dataset from heterogeneous sources. In this article I
describe the principles behind sunstardb, the data structures and programming
interfaces, as well as use cases from solar-stellar connection research.
