AMPL vs. Ada vs. Python vs. R Comparison Chart

Ada is a state-of-the-art programming language that development teams worldwide are using for critical software, from microkernels and small-footprint, real-time embedded systems to large-scale enterprise applications, and everything in between. Why use Ada? In short, because you want to write reliable and efficient code, with confidence that it works, and not waste time and effort in the process. Ada is unique among languages in how it helps you detect and eliminate bugs early in the software life cycle when they are least expensive to correct. And as evidenced by the many successfully fielded applications that need to meet a hard time or space constraints, Ada helps you build software that is reliable, safe, and secure without sacrificing performance. At the technical level, Ada has everything you might expect in a modern language. Concurrent programming features, including support for multicore.

R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed.