It took me a while to figure out which stats program worked for me. I am currently a mostly SAS user, but spent my undergrad (and taught undergrads) with SPSS and Master's with R. Given the increasing interest in using R for data analysis, perhaps my experience with R will be helpful for anyone looking to test those waters.
SPSS was great, but during my Master's, I gave R a shot. It was a steep learning curve for someone who had up till then been using SPSS (and some messing around with VBA on Excel). At times I felt I was spending more hours than I should doing basic things. It was (and others have said this too) like learning a new language, but not a particularly intuitive one. Outputs were not pretty, loop functions were confusing.... The one thing that put a smile on my face was having beautiful plots come out from ggplot2 [Sidebar: I cringe thinking back to a time a few years ago when I used ggplot2 to come up a graph that looked cool, but was not particularly helpful for one of my presentations]. Eventually, a lot of guided manuals for R came out and it became easier to learn it in a more structured manner. I would recommend making R a secondary data analysis program you're learning/using if you're concerned with making quick progress and if you're new to programming. SPSS is still a very useful program!
Once some of the basics have been relatively mastered, R is great tool, particularly in data visualization. The graphs are easily editable, which is a major plus. In sum, R is a useful program, but not necessarily one you can learn quickly.
However, I still wasn't comfortable with R. Until, my friend John Kiat suggested SAS and it changed how I worked. It made me more efficient, it made data organization a breeze [Thanks John!], and freed up time I spent organizing/recoding my datasets "just right". It made me write better code probably because it wasn't a program that felt like I was taking a shot in the dark at times.
SAS also came at the right time. I was pre-registering studies and wanted to be able to eventually share codes, but was in no way confident with my R-based codes. SAS was more intuitive and the steep learning curve from R made the transition to SAS (and even Stata) pretty smooth for me, but I suspect a transition from SPSS to SAS is not as difficult as jumping into R. I think R requires a lot of "unprogramming" from the SPSS-style of data analysis. This is not a bad thing, but for some people it can be a frustrating experience in the midst of grad school.
If you haven't tried SAS, give it a go! If you have some time, learn R.