The system uses bi-temporal schema concepts, which means that data in the system understands the time period when it was valid in the real world, as well as the time that it was stored inside the database. Knowing these two times provides the capability to look at every piece of market and transaction data through time. This future proofs the system against most new regulatory reporting requirements since most regulation includes the ability to look back and track the state of a particular market order, fill or trade over time.
Typical relational schemas do not provide this capability. They rely on logging the pieces of data they are interested in. Most new regulations require access to the history of data elements inside of the relational database. If these elements are not logged by the applications logging software then the only way to retrieve their state at a past point in time is to load a backup of the database. This is one of the reasons why responding to new regulatory initiatives is often an expensive undertaking. A bi-termporal schema tracks the state of every attribute though time, eliminating the need go back and reconstruct history for unlogged pieces of information.