I think that you have, at least, the following major options for your data analysis scenario:
Use big data-enabling
R packages on your local system. You can find most of them via the corresponding CRAN Task View that I reference in this answer (see point #3).
Use the same packages on a public cloud infrastructure, such as Amazon Web Services (AWS) EC2. If your analysis is non-critical and tolerant to potential restarts, consider using AWS Spot Instances, as their pricing allows for significant financial savings.
Use the above mention public cloud option with
R standard platform, but on more powerful instances (for example, on AWS you can opt for memory-optimized EC2 instances or general purpose on-demand instances with more memory).
In some cases, it is possible to tune a local system (or a cloud on-demand instance) to enable
R to work with big(ger) data sets. For some help in this regard, see my relevant answer.
For both above-mentioned cloud (AWS) options, you can find more convenient to use
R-focused pre-built VM images. See my relevant answer for details. You may also find useful this excellent comprehensive list of big data frameworks.