Recently, I’ve worked on two projects (Power Hungry, Hot or Not) which (among other things) collect write-once data over time, and graph the results. The projects collect very different data, but this task was painful enough in postgres that I ended up switching to a temporal database for the second go, and it made the data collection & querying much easier. What follows is a brief discussion of the problems I faced with postgres, and how moving to RRD solved them.
I finished my first significant electronics project in a while: Power Hungry. The idea is that I use sensors to monitor the actual voltage & amperage usage of various devices in my apartment, and I wirelessly transmit that to a base station, which calculates various statistics. The results are then beamed to my linode server, where I have some graphs of the data. The ultimate goal is to use this data to reduce my overall energy usage, but for now I’m just working on establishing a baseline, so I can best judge the effectiveness of whatever changes I make. The results so far, though, are fairly interesting.