Could you explain the difference between `STAR`, `KALLISTO`, `SALMON` etc. to experimental Biologist/non-bioinformatician.

If possible, the pros and cons of each pipeline. 

**Edit below**

 ***I ask this because three of my colleagues use this 3 difference tools for RNASeq. Basically to answer the same type of biological questions.***
Regarding the pros and cons of the programs, you might find this article useful: 
[https://www.nature.com/articles/s41598-017-01617-3][1]
It finds that kallisto and Salmon produce near identical results, and that STAR (with HTseq for producing gene counts) is less accurate (due to some of the reasons explained above). In terms of speed/memory requirements, the difference between programs is substantial. In recent benchmarking of kallisto vs. STAR on workflows for single-cell RNA-seq 
[https://www.biorxiv.org/content/10.1101/673285v2][2]
we found that kallisto was 2.6 times faster than STAR. More importantly, kallisto used much less memory, in some cases 15x less RAM than STAR. This makes it possible to run kallisto on a laptop rather than a server, and facilitates reproducible workflows.

  [1]: https://www.nature.com/articles/s41598-017-01617-3
  [2]: https://www.biorxiv.org/content/10.1101/673285v2