applied ML research here also -- a lot of interactive (but highly parallelizable) modeling, graphing. Using medium-size data sets around 3-4GB in ram, by the ti

applied ML research here also -- a lot of interactive (but highly parallelizable) modeling, graphing. Using medium-size data sets around 3-4GB in ram, by the time you forked it a few times, you easily end up beyond the m4.10xlarge or c4.8xlarge limits. IMO theres an awkward space between small data and big data where it isn't really worth spending a long time to treat it like a real "big data" problem, and the x1 instance gives you an easy-out.