There are many SEM software packages from which to choose (e.g., AMOS, LISREL, Mplus, EQS, Calis, stata, R libraries such as lavaan or sem). In general, your sample size is not an issue that would govern the package that is best suited for you. Instead, matters such as: scale of your variables, missing data, complexity of model , and assumption set (for example, is covariance based sem more suitable or is partial least squares sem more suitable) are far more important.
Most of the comparisons I've seen suggest that there aren't noteworthy differences among the packages compared with respect to accuracy of parameter estimates or fit indices. Rather, the differences have to do with user features, and ability to address some of the issues named above.
Here are some comparisons, if you care to chase this further:
Article A Review of Software Packages for Structural Equation Modeli...
The answer to this question is simple. Please do not get confused. There is no logical relationship between the sample size and the type of software. Most commercial and non-commercial software used these days, depending on your hardware system, can support this sample size.