Since R is an in-memory language, it sometimes has a reputation of not being able to handle big data. However, using some creativity and strategic thinking, you can use big data in your predictive analytics projects quite successfully.
In addition to the preceding approaches, there are currently a number of alternative approaches you may wish to research, such as:
There are packages available that avoid storing data in memory. Instead, objects are stored on hard disk and analyzed in chunks. As a side effect, the chunking also leads naturally to parallelization, if the algorithms allow parallel analysis of the chunks in principle. You can search: Revolution R Enterprise for some background on the topic.