The best known columnar RDBMS is surely Sybase’s IQ Accelerator, evolved from a product acquired in the mid-1990s. Problem – it doesn’t have a shared-nothing architecture of the sort needed to exploit grid/blade technology. Whoops. The other recognized player is SAND, but I don’t know a lot about them. Based on their website, it would seem that grids and compression play a big part in their story. Less established but pretty interesting is Kognitio, who are just beginning to make marketing noise outside the UK. SAP’s BI Accelerator is also a compressed columnar system, but operates entirely in-memory and hence is limited in possible database size. Mike Stonebraker’s startup Vertica is of course the new kid on the block, and there are other columnar startups as well whose names currently escape me.
As a plausibility argument for the benefits of columnar systems, Mike likes to trot out three “tick processing” software offerings (that’s in the stock price sense of “tick”) – Vhayu’s Velocity, Sungard’s FAME, and Kx’s kdb. I know even less about these than I do about SAND, but I’m conjecturing they’re time series data stores rather than full RDBMS. Mike is less eager to talk about Required Technologies, a failed columnar RDBMS startup that he was involved in, and which is the pretext for (through no fault of his) TransRelational hype.
If columnar systems take off, be prepared for a lot of “We do that too” claims from mainstream DBMS vendors. Oracle and other conventional relational DBMS do feature bit-mapped indices. But while they’re more versatile than pure columnar systems, they won’t do columnar things as efficiently as the purists (or near-purists) do. Full-text indices are closely akin to bit-maps– e.g., SAP’s BI Accelerator grew out of TREX – but obviously it would not be accurate to call them “columnar” (or, for that matter, “relational”).