Analyzing Big Data on Macbook?

I just received a new ultra-portable MacBook 2015.  I primarily use it for email and word processing but have also been testing it out using SAS running locally on the laptop.  SAS currently does not have a native Mac OS version so I am running it inside a Windows Virtual Machine (VM) using Parallels.  There have been many reviews criticizing how under powered the new MacBook is due to its Intel Core M processor.  I initially thought that running a Windows App through a VM such as SAS that normally brings servers to its knees would not work.  To my surprise, it worked quite well.  

Besides being able to work interactively with SAS, I was curious how it would perform running multiple SAS jobs analyzing data in batch mode.  I needed hard numbers to compare so I ran some benchmark tests in comparison with a server with 8 CPUs and 30GB of RAM as compared to this little laptop with 1 CPU and 1GB of RAM.  The MacBook actually has dual core CPU and 8GB of RAM, but the VM only allocated 1GB for Windows and SAS.  This does not seem fair and is not an "apple to apple" :) comparison.   The result which I show in this video was surprising in that the MacBook outperformed the server in several cases.  In general, it performs faster when running a single program at a time.  I even performed well when submitting two SAS jobs at once.  However, it started to lag behind the server when submitting five jobs simultaneously.

SAS does utilize CPU to perform analysis but it is also very I/O intensive.  My theory for this is that the new MacBook utilizes a new PCIe bus for its SSD drives which boosts I/O performance against traditional hard drives with SATA bus on most servers.  There may be many other factors such as other users on the server and which SAS PROC you use, but this test does show how you can perform powerful analytics even when on an airplane disconnected from server farms while using the new ultra-portable MacBook.