Folks,
I'm building a real-time, very short-frequency trading platform. The platform needs a backend for storing exchange ticks (quotes) and I think MonetDB could be that platform.
My ultimate attraction is the vertical decomposition that sets MonetDB apart. It's the approach taken by KDB
http://www.kx.com/products/kdbplusfaq.php http://cs.nyu.edu/cs/faculty/shasha/papers/sigmodpap.pdf
and that has already proven immensely effective.
My personal need is in searching for matching subsequences in other time series (k-NN?) which would require me to compute the Euclidian distance between points, etc.
Martin suggested that I build a time series extension module which is fine with me (see http://wagerlabs.com/resume.pdf) I have several questions before I embark on this project...
I don't have a clear understanding of how MonetDB managed indexes. If I'm dealing with timestamp, price and volume and need to search either would I need to build indexes on the three columns?
I believe MonetDB supports range queries. Could I just store timestamp as an integer such as YYYYMMDDHHSS and do a range query on that?
How would I go about building the time series extension module? Would I need to add custom search accelerators to build a specialized index on the fly?
Thanks, Joel