To be honest, that rationale was applied after the fact. One of the many backend iterations that I wrote, prior to the mmap backend, was using read() and frien

To be honest, that rationale was applied after the fact. One of the many backend iterations that I wrote, prior to the mmap backend, was using read() and friends and after porting the code to mmap-based I/O the output was faster on both warm and cold disk buffers. I was planning a big blog entry just on the backend options that we used since I tried several combinations of I/O backends with different numbers of reader threads in our profiling dataset with different I/O elevator scheduling algorithms (switching the algorithms, disappointingly, had a negligible effect on performance and I/O throughput degraded when increasing the number of reader threads to more than twice the number of active cores) -- but that kind of slipped into the background as we started filling out the bits of the database to give it an acceptable level of robustness. The hashing scheme that we're using is optimized for keeping a tight memory profile -- and hence disk profile. Again, much of the rationale was applied after the fact to try to explain the results of profiling. At first we tried things with B-trees and with the combination of the VM's paging and our access patterns the hashes were faster. It's possible that if we were using the direct I/O APIs that many databases use and doing all of our own caching internally that we'd be able to achieve higher throughput with B-trees. In our case, letting the OS handle our caching and keeping identical C++ structures to our disk structures simplified the code enough to merit leaving things this way for the time being. At the end of the day, our product is a recommendation engine, not a database, so we'd like to keep the codebase relatively lean. So, yeah, a lot of the explanations are applied after the fact from what I know of systems programming, but the results were validated through actual test runs through multiple competing backend implementations. The one we described gave the best overall results.