MBP Retina 8GB vs 16GB for data analysis - R, Python large files?

I increasingly find myself working with graph data (Neo4J, Gephi) and document databases (Mongo, CouchDB) as well as using R for clustering and analysis and Python to munge fairly large files of 1GB or larger.
8GB would probably serve me well and coming from a machine with 4GB will feel like plenty, but I suspect that I am the kind of use who would get his money worth out of 16GB.
In addition to this I will be running a Windows VM for Office Excel/VBA work and to stats packages for university very frequently.
Is getting the upgraded model worth it? Or will I not notice any difference.
Thanks,
David

I would say you will want the 16GB for a few reasons. You are working with memory-intensive datasets, and also you are running a virtual machine. VMs tend to use up a lot of RAM since it means you are running two complete OSs at the same time, on top of any other apps you might be running.
The third reason is that the Retina models cannot be upgraded after purchase. You would not want to have an 8GB forever if you discovered that your future work needed a bit more memory. You've already demonstrated doing some tasks that can be RAM-intensive, just max out the RAM and never worry about it again.
If you still have doubts, learn how to analyze RAM usage and particularly swap file behavior in Activity Monitor. If your Mac is already paging to swap files frequently, you already need the RAM. If you do work for several days and swap paging activity is low, you don't need the RAM.

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