Well, Spark does allow you to accomplish distributed workloads for certain forms of computation. But it's limited to those forms of computations (streaming, map

Well, Spark does allow you to accomplish distributed workloads for certain forms of computation. But it's limited to those forms of computations (streaming, map-reduce). It also has a large operational footprint. It's also lamentable that distributed code that uses Spark looks nothing like its non-distributed counterpart. Something very much like Spark map-reduce can be implemented in ~100 lines of Unison code: https://www.unison-lang.org/articles/distributed-datasets/ https://www.unison-lang.org/articles/distributed-datasets/ Some videos on Unison's capabilities over and above Spark: Distributed programming overview: https://www.youtube.com/watch?v=ZhoxQGzFhV8 https://www.youtube.com/watch?v=ZhoxQGzFhV8 Collaborative data structures (CRDTs): https://www.youtube.com/watch?v=xc4V2WhGMy4 https://www.youtube.com/watch?v=xc4V2WhGMy4 Distributed data types: https://www.youtube.com/watch?v=rOO2gtkoZ3M https://www.youtube.com/watch?v=rOO2gtkoZ3M Distributed global optimization with genetic algorithms: https://www.youtube.com/watch?v=qNShVqSbQJM https://www.youtube.com/watch?v=qNShVqSbQJM