In the Increasing need for Data Science, Data languages are among the most looked out for, generally the fight between SAS & R has been age old now. But it looks like R has taken the lead. With its libraries and infinite graphical abilities and its open source nature R is downloaded like Hot cakes.
R has likewise simpler Machine Learning Algorithms and outstanding Graphical abilities, R as compared to SAS and SAS has a less steep learning curve.
Ease of Learning
R has the steepest expectation to absorb information among the 3 Programming recorded here. It obliges you to learn and comprehend coding. R is a low level programming Programming and henceforth straightforward methodology can take longer codes.
SAS as compared to R is easy to learn and has its syntax similar to that of SQL.
R processes everything in memory (RAM) and consequently the calculations were restricted by the measure of RAM on 32 bit machines. This is not true anymore. Each of the three Programmings have great information dealing with abilities and alternatives for parallel calculations. This I feel is never again a major separation. Graphical Abilities
R has the most exceptional graphical capacities among the three. There are various bundles which give you progressed graphical capacities.
SAS Has decent Functional graph abilities but they are not very open to customization
Trying not to sound R biased here, but we’ll have to say that R has better Data science abilities than SAS, but SAS being General Purpose may take the upper hand in general terms.