Not to be snarky, but we announced Julia in Feb 2012, which is less than 5 years ago. Unless you happened to be in the MIT class that used Julia in the Fall of

Not to be snarky, but we announced Julia in Feb 2012, which is less than 5 years ago. Unless you happened to be in the MIT class that used Julia in the Fall of 2011, you're probably overestimating how long you've been following the project. If you're comfortable using R and the tooling and performance it offers, you should probably keep using it. Julia isn't just about big data, but it does tend to appeal to people who are struggling with problems that are sufficiently hard that their old tools left them in a world of pain. That pain may comes from size, complexity, CPU-intensiveness, or need for more language expressiveness (a hard thing to define). In particular, Julia offers a unique combination of productivity and speed for numerical work that can't be found anywhere else.