Creating a custom datastore may seem like a bad idea when such great tools like Postgres, MongoDB, CouchDB, etc. are available in their open source goodness as well as good commercial products such as Datomic, AllegroGraph, Stardog, etc. Still, frustration of not having just what I needed for a project (more on requirements later) convinced me to spend some time building my own datastore based on some available open source libraries. Much of the motivation for my work developing kbsportal.com is to make possible the development of a larger turnkey information appliance. I have been using MongoDB for this, but even with an application specific wrapper MongoDB has been a little awkward for my requirements, which are: I want a reasonably efficient document store that supports the usual CRUD operations on arbitrary Clojure maps (which can be nested to any depth). Clojure maps are basically what I use to contain and use data so I wanted a datastore that supports this, simply. I want all ...

I wrote last July about my small bit of code on github that wrapped the Microsoft Bing Search APIs. I recently extended this to also wrap the Translation APIs using the open source project microsoft-translator-java-api project on Google Code . I just provide a little wrapper for the microsoft-translator-java-api project and if you are working in Java you should just use their library directly. Hopefully this will save you some time if you need to use the translation services. The free tier for the translation services is currently 2 million characters translated per month.

I spent 10+ years using large frameworks, mainly J2EE and Ruby on Rails. A large framework is a community and set of tools that really frames our working lives. I have received lots of value and success from J2EE and Rails but in the last few years I have grown to prefer micro frameworks line Sinatra (Ruby) and Compojure + Noir + Hiccup (Clojure). Practitioners who have mastered one of the larger frameworks like Rails, J2EE, Spring, etc. can sometimes impressively and quickly prototype and then build large functioning systems. I had an odd thought this morning, and the more I mull it over, the more it makes sense to me: large frameworks seem to be optimized for consultants and consulting companies for the quick kill : get in, build the most impressive system possible with the minimum resources, and leave after finishing a successful project. This is an oversimplification, but seems to be true in many cases. The flip side to the initial productivity of large frameworks is a very rea...