I'm in the process of building a social Bayesian suggestion engine. I've coded out a large portion of it from scratch in PHP following an MVC design pattern, but I'm starting to wonder if this is the right environment for doing some Bayesian inference. Will good ol' MySQL work on a grand scale?<p>Reading about the obstacles Hunch has encountered has made me reconsider PHP, but that's what I know best. I'm fairly proficient in Python, so it wouldn't be such a leap to use Django, but I'd prefer not to if there's not a big performance difference. I've looked at MongoDB and it looks like I could replace MySQL without requiring me to rewrite too much of my code base. Node.js looks pretty exciting, but I know very little about it's proper application or whether it's stable enough.<p>I'm up for learning to work in a new environment if there's something that's just _right_ for the job. Any suggestions?
Python is generally faster than PHP, particularly if you're not using APC or Zend. But the real benefit of using Python is the vast amount of software out there to do so many things. For example, PyBrain (<a href="http://pybrain.org/" rel="nofollow">http://pybrain.org/</a>) may be right up your alley. The book "Programming Collective Intelligence" is all Python-based, and covers a wide range of algorithms including classifiers and so on, some of which use SQL backends. I thought the book was awesome, practical and inspiring, but I'm not a hardcore AI person.<p>MySql vs NoSql: you may find that sql is totally adequate for what you're trying to do. You may be able to factor the data access out to a data layer such that you can switch the underlying storage without too much work.<p>If your goal is to just get it finished, go with what you know. If your goal is to grow and/or earn street cred, leave your comfort zone asap!