One thing I wonder is how far do graph databases actually take you? I take the "thing" of a graph database to be to give me all links with a single access (that is all links of a node are in a single data set). On the other hand, in a classical SQL setup links would probably be modelled in a table with one row per link.
But still, even if I can get all links of a node with one access, it seems to me memory will be too scarce in most cases. Let's say I want to consider all nodes that are three steps away, and every node has 100 outgoing links. That's 100^3 nodes to consider already. Or in the second step, 100^2 nodes, so we would have to access the db 10000 times to get all nodes of the third step.
What I am getting at: it seems to me for really interesting graph computations it will usually still be necessary to create some specialized/compressed model to fit all the data into main memory.
Comments
One thing I wonder is how far do graph databases actually take you? I take the "thing" of a graph database to be to give me all links with a single access (that is all links of a node are in a single data set). On the other hand, in a classical SQL setup links would probably be modelled in a table with one row per link.
But still, even if I can get all links of a node with one access, it seems to me memory will be too scarce in most cases. Let's say I want to consider all nodes that are three steps away, and every node has 100 outgoing links. That's 100^3 nodes to consider already. Or in the second step, 100^2 nodes, so we would have to access the db 10000 times to get all nodes of the third step.
What I am getting at: it seems to me for really interesting graph computations it will usually still be necessary to create some specialized/compressed model to fit all the data into main memory.