They have used adjacency lists, which looks strange to me — this is a common way of representing graph data in memory, but doesn't map well to the relational model. I have used "extreme normalization", where all edges are represented as many-to-many relationships with associative tables.
Though I stored document relationships and social graphs, not semantic graphs, as they describe in this paper. I have little experience with semantic graphs — perhaps, they have different requirements.
How many joins did it have (sounds very joinery :-D)/or how deep was your graph? Presumably it was doing full table scans for everything - sounds very interesting anyway.
Though I stored document relationships and social graphs, not semantic graphs, as they describe in this paper. I have little experience with semantic graphs — perhaps, they have different requirements.