  Data processing systems roughly group into families such as relational,
array, graph, and key-value. Many data processing tasks exceed the capabilities
of any one family, require data stored across families, or run faster when
partitioned onto multiple families. Discovering ways to execute computation
among multiple available systems, let alone discovering an optimal execution
plan, is challenging given semantic differences between disparate families of
systems. In this paper we introduce a new algebra, Lara, which underlies and
unifies algebras representing the families above in order to facilitate
translation between systems. We describe the operations and objects of
Lara---union, join, and ext on associative tables---and show her properties and
equivalences to other algebras. Multi-system optimization has a bright future,
in which we proffer Lara for the role of universal connector.
