Is the R language suitable for Big Data R has many libraries which are aimed at Data Analysis (e.g. JAGS, BUGS, ARULES etc..), and is mentioned in popular textbooks such as: J.Krusche, Doing Bayesian Data Analysis; B.Lantz, "Machine Learning with R".

I've seen a guideline of 5TB for a dataset to be considered as Big Data.

My question is: Is R suitable for the amount of Data typically seen in Big Data problems? 
Are there strategies to be employed when using R with this size of dataset?
Actually this is coming around. In the book R in a Nutshell there is even a section on using R with Hadoop for big data processing. There are some work arounds that need to be done because R does all it's work in memory, so you are basically limited to the amount of RAM you have available to you.

A mature project for R and Hadoop is RHadoop

RHadoop has been divided into several sub-projects, rhdfs, rhbase, rmr2, plyrmr, and quickcheck (wiki).