So I'm doing a lot of academic reading around databases, and people have been thinking about this sort of thing for a while. Here's one approach: > In this pap

So I'm doing a lot of academic reading around databases, and people have been thinking about this sort of thing for a while. Here's one approach: > In this paper, we study the complementary approach, addressing index maintenance as part of query processing using continuous physical reorganization, i.e., cracking the database into manageable pieces. The motivation is that by automatically organizing data the way users request it, we can achieve fast access and the much desired self-organized behavior. > The cracking approach is based on the hypothesis that index maintenance should be a byproduct of query processing, not of updates. Each query is interpreted not only as a request for a particular result set, but also as an advice to crack the physical database store into smaller pieces. http://stratos.seas.harvard.edu/files/IKM_CIDR07.pdf http://stratos.seas.harvard.edu/files/IKM_CIDR07.pdf The references are also pretty good. edit: Here's one more specifically about (de)normalization: http://stratos.seas.harvard.edu/publications/main-memory-adaptive-denormalization http://stratos.seas.harvard.edu/publications/main-memory-ada... But it's much newer and lighter on info.