you can analyze the statistics of when/where specific people are most probable to check-in and pre-load (or even pre-calculate) the data in advance.
For example, starting at ~9pm the data about check-ins into library may be safely unloaded to disk (the probability of needing this data is low and reading from disk for whose rare cases would do just fine) and be replaced in memory with data about check-ins to clubs, etc...
For example, starting at ~9pm the data about check-ins into library may be safely unloaded to disk (the probability of needing this data is low and reading from disk for whose rare cases would do just fine) and be replaced in memory with data about check-ins to clubs, etc...