4 ms·

Would love to hear more on your usage as a graph database, especially in light of http://static.googleusercontent.com/media/research.google.com/en//pubs/archive

• atemerev 11y ago
  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.
  • andy_ppp 11y ago
    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.
    • atemerev 11y ago
      About 1.5 million nodes (not that big), most of queries followed 3-4 edges. Joins are good. :)