"The consequence of this difference is that your guidelines for APIs are different. In process calls can be fine-grained, if you want 100 product prices and ava

"The consequence of this difference is that your guidelines for APIs are different. In process calls can be fine-grained, if you want 100 product prices and availabilities, you can happily make 100 calls to your product price function and another 100 for the availabilities." While this is true, in fact for efficiency reasons it's often better to treat even local dispatch like it's "network" -- chasing pointers and doing things one at a time in a loop is far less efficient on a modern architecture than doing things in bulk and vectorized. Non uniform memory hierarchies, caches, branch predictors, SIMD, and now GPUs, etc. all tend to reward working with data in batches. If I were to think of a "pure" model of computation that unified remote and local it would be to treat the entire machine in terms of the relational data model, not objects. To treat all data manipulation and decisions like a query. And to ideally in fact have the same concept of a query optimizer / planner that a DBMS has, which is able to make decisions on how to proceed based on the cost of the storage model, the indexes, etc. because it has a bigger picture of what the programmer is trying to accomplish.