The rise of multicore processors and could computing is putting enormous pressure on the software community to find solutions to the difficulty of parallel and distributed programming. At the same time, there is more-and more varied - interest in data-centric programming languages than at any time in computing history, in part because the inherently unordered nature of these languages encourages programs that parallelize easily. This juxtaposition raises the possibility that the theory of logic programming and deductive database languages can provide a foundation for the next generation of parallel and distributed programming languages.

In this talk I will reflect on my group's experience over seven years using Datalog extensions to build networking protocols and distributed systems. I will introduce a temporal logic called Dedalus, and our plans to build upon it in our upcoming Bloom language for cloud programming. Time permitting, I will also discuss a number of theoretical conjectures we have formulated, including the CALM conjecture relating the distributed systems notion of eventual consistency to monotonicity in logic.

This is an adapted version of a keynote at ACM PODS.