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Everyone's talking about graph databases lately. Who hasn't designed some relational data structure and then refined it a bit and tweaked it a bit and ended up

Everyone's talking about graph databases lately. Who hasn't designed some relational data structure and then refined it a bit and tweaked it a bit and ended up with some sort of adjacency-list monstrosity and the realization that the relational underpinnings for that are rather awkward? I'm really looking forward to reading more about Pregel. In the meantime I just found Greg Malewicz's PhD thesis. He seems very interested in scheduling, which must be crucial to Bulk Synchronous Parallel: http://www.cs.ua.edu/~greg/publications/Malewicz_PhD.pdf http://www.cs.ua.edu/~greg/publications/Malewicz_PhD.pdf

Tichy 17y ago
Representing graphs in relational databases seems straightforward enough (not that I have done, but I have an opinion nevertheless). Accessing it efficiently if you want to traverse a graph seems to be the hard problem. I wonder if there are ANY good solutions at all, short of loading the whole graph into memory. Otherwise I suppose one would need a good heuristic for caching the edges and vertices that are most likely to be accessed?