Depends on what you want to do and what skills that you have. I suggest that you edit your question if you want more useful responses.

In my opinion "R" is better, it's a free software.

Also, it's easy compared with other software.

X (substitute X by either SPSS or by R, as you wish) is the better software when

• you are experienced/skilled in X
• your collegues/company use X
• X is the standard in your field of research
• only X provides the functionality you need
• you already have working toolbox for X
• you can more easily afford/access X
• it's easier for you to get more (competent) help in X

Definitely R. It should be noted, R is free and has no analytical limits.

It depends. SPSS is more versatile then most people think or know. SPSS has its own programming language, but most people don't know about it. Most SPSS commands are running with parallel processing.

I have run very complex data handlings with SPSS that are hard to do in R. I can create very large data sets in SPSS that would not fit in the CPU cores as required by R. SPSS also can be integrated with R and Python and benefit from all programs at the same time, but as most have said SPSS is not free.

SPSS is also a misleading shortcut. SPSS has many additional packages that most never have seen or heard about. Have you worked with SPSS Tables or SPSS Catagories, SPSS Regression Trees? In Data Mining and Regression Trees, you have options of handling missing values, R does not have.

So experience and expertise might be the limits to using a program.