IIUC, the tree structure is the very thing they're trying to store and query -- it's not merely an artefact of a data structure that they're using to store something else (the way a B+ tree or binary tree used to store, say, a set of product names would be). If their tree has long paths, it has long paths.
replyAuthor here. That’s right — the challenge was representing a tree in an existing SQL database that we’d chosen for its pricing model. I think encoding a B-tree in SQL would be a lot less fun even than what we did.
replyThe nice thing with skip lists, is all 'rungs' of the list are stored in an array for a given node, so there's a lot less pointer chasing.
replyThe not so nice thing about it is that you have to pre-guess how deep your tree will be and allocate as many slots, or otherwise itll degrade into a linked list when you run out of rungs, or you end up wasting space.
You don't really have to pre-guess the number of rungs -- you can just have a linked list of them and add a new rung "on top" when necessary, because you always start at the top rung, and only ever move sequentially along a rung, or step down to the rung immediately below. The overhead of pointer chasing is pretty small because there will only be O(log n) rungs; you move between rungs roughly often as you move along them.
replyAlso you can freely choose the "compaction rate" (base of that logarithm) to be something other than 2 -- e.g., choosing 4 means half as many rungs (but ~twice as much wandering along each rung).