There are many reasons to use an eventually-consistent database — like Riak, Voldemort, or Cassandra — including increased availability, lower latency, and fault-tolerance. However, doing so requires a mental shift in how to structure client applications, and certain types of traditional data-structures, like sets, registers, and counters can’t be resolved simply in the face of race-conditions. It is difficult to achieve “logical monotonicity” except for the most trivial data-types.
That is, until the advent of Convergent Replicated Data Types (CRDTs). CRDTs are data-structures that tolerate eventual consistency. They replace traditional data-structure implementations and all have the property that, given any number of conflicting versions of the same datum, there is a single state on which they converge (monotonicity). This talk will discuss some of the most useful CRDTs and how to apply them to solve real-world data problems.