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Im normally a kdb+ kind of guy when it comes to managing huge amounts of streaming and historical tick data, the performance is great, the app small and clean and the language Q terse with just enough to get the job done.  On the downside Q is a bit cryptic, and the documentation is brutally terse.. though readable.

I decided to do a bit of googling to see whether another product was out there that might be useful, and came across StreamBase, which is the commercial outgrowth of some research projects at MIT – Aurora, Borealis and Medusa.  These projects were led by Michael Stonebraker, who invented {|discovered?} ingres and postgresql databases in their original form.  His short blurb on Stream processing – Data Torrents and Rivers – is a worthwhile introduction.

The StreamSQL language spec seems to be independent of StreamBase, as it has its own site which describes the language –

StreamSQL does seem to fall short of being a fully independent spec, and I wanted to make some comment on this… because the world really does need an accessible stream processing language that acts in the same way as SQL – I love Q but I just dont see your average quant developer having time to grok it when they already have to learn C++/Perl/Python/Matlab/R and I guess soon ruby [until lisp becomes the 100year language].

Heres my Open Letter to the StreamSQL people –

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