The system uses a bi-temporal schema, which means that every piece of data in the system understands the time period when the data was valid in the real world time) as well as the time period when a fact stored inside the database was known (transaction time). This provides the capability to look at every piece of the market and transaction data through time. This future proofs the system against most new regulatory requirements since most regulation includes the ability to look back and track the state of a particular 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 current 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 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.