Distributed data structures is an interesting idea, but I’m not sure this particular implementation is the right abstraction level for many problems. These sor

Distributed data structures is an interesting idea, but I’m not sure this particular implementation is the right abstraction level for many problems. These sorts of things form a spectrum from low level message passing all the way to a full fledged database. Some things in between are abstractions like MapReduce which still gives a lot of control, but also gives you fault tolerance and lower configuration of your cluster to run different applications. Another abstraction in this space that is just a bit higher than ordinary message passing are systems like Kafka and RabbitMQ which give additional guarantees over plain message passing using sockets as well as less configuration to set up/remove machines. One thing a lot of the more successful abstractions in this space seem to have is a pretty clear line between which parts of the system are local and which are distributed. It seems like this system doesn’t have as clear of a demarcation which would make understanding performance much more difficult. Databases can also have this problem since they do a lot of low level performance tuning automatically, but at least they provide a very high level of abstraction for applications to work with. This seems like it could end up being confusing to tune without providing a nice high-level interface like databases.