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The "solar-stellar connection" began as a relatively small field of researchfocused on understanding the processes that generate magnetic field in starsand which sometimes lead to a cyclic pattern of long-term variability inactivity, as demonstrated by our Sun. This area of study has recently becomemore broadly pertinent to questions of exoplanet habitability and exo-spaceweather, as well as stellar evolution. In contrast to other areas of stellarresearch, individual stars in the solar-stellar connection often have adistinct identity and character in the literature, due primarily to the rarityof the decades-long time series that are necessary for studying stellaractivity cycles. Furthermore, the underlying stellar dynamo is not wellunderstood theoretically, and is thought to be sensitive to several stellarproperties, e.g. luminosity, differential rotation, and depth of the convectionzone, which in turn are often parameterized by other more readily availableproperties. Relevant observations are scattered throughout the literature andexisting stellar databases, and consolidating information for new studies is atedious and laborious exercise. To accelerate research in this area I developedsunstardb, a relational database of stellar properties and magnetic activityproxy time series keyed by individual named stars. The organization of the dataeliminates the need for problematic catalog cross matching operations inherentwhen building an analysis dataset from heterogeneous sources. In this article Idescribe the principles behind sunstardb, the data structures and programminginterfaces, as well as use cases from solar-stellar connection research.

Sunstardb: a database for the study of stellar magnetism and the solar-stellar connection