It's well understood how logical clocks can be used to capture the order in which events occur. By extension, vector clocks encode when an event occurred across a distributed system. GoshawkDB reverses this idea: by analysing the dependencies between transactions, each participant calculates a vector clock that captures the constraints necessary to achieve strong serializability. The vector clocks from the different participants in a transaction can then be combined safely using the same techniques as CRDTs. This allows GoshawkDB to achieve strong serializability without imposing a total global ordering on transactions.

In this talk I will demonstrate these algorithms: what dependencies do we care about between transactions, how can we capture these with Vector Clocks, how we can treat Vector Clocks as a CRDT, and how GoshawkDB uses all these ideas and more to achieve a scalable distributed data store with strong serializability, general transactions and fault tolerance.