From memory (haven’t used it since 2014b), parfor in MATLAB has a worker pool, so essentially different MATLAB processes, rather than threads, so the closer Julia equivalent would be a @distributed for loop.
I recently answered a question on StackOverflow related to this here which might be of interest. Generally the most efficient way of parallelising will depend quite heavily on your actual problem (complexity of calculations, uniformity of time taken for individual chunks of the calculation, required memory access patterns, system that you’re looking to run the code on), so it’s hard to comment based on very abstract examples.