Now we're talking optimizing for a hugely multidimensional system here. Expressiveness: If you've aiming for a large team, try to work with a language that ena

Now we're talking optimizing for a hugely multidimensional system here. Expressiveness: If you've aiming for a large team, try to work with a language that enables large scale services and large teams - also in the long run, strongly typed languages will work out better for this case, Java / Scala being the obvious candidates. But if you go down a microservices route, other choices might work too. Niche stars: Some languages have obvious strengths in certain niches, depending on what you want to build. Machine learning - Python, Microservices - Go, isomorphic JS web servers - Node. Performance: Very many requests -> closer to the machine. Note that JITs have skewed this equation somehow towards being able to use scripting language, but it still generally stands, because if for some reason you can't track, code is falling out of the optimizer after a one line change, you're still screwed. Closer to the machine is more predictable. Maturity / Current traction / Traction curve: Brand new is shiny and attracting bleeding-edge devs (making hiring easier), but be prepared to be the first one with a problem or having lots of devs around who love tech more than results and are gone for the next shiny thing in half a year. Lots of current traction is good, rather don't choose languages that are great but on the path down (Ruby). Be extra careful in choosing too exotic languages, you won't be the first company dying from not finding any devs for your ageing Groovy on Grails stack. Availability: PHP and Java are safe bets, but it's much harder to separate the wheat from the chaff developerwise. Languages like Go or Clojure will find you more driven devs usually because they're not usually taught at university. Caveats: see above. Lots and lots of other variables here, just some of the larger thinks to think about.