Extracting data from a fully normalized remote DB can be costly. We can simplify and speed-up the process by effectively caching the set of pending transactions for use in the upcoming transactions dashboard. To do so, we will create a single table with denormalized data for the current pending transactions. As soon as a transaction is mined, it will be marked for removal from this DB after a short period (e.g. an hour).
Alternatively, we may opt for an in-memory data structure, completely omitting SQL usage.
Extracting data from a fully normalized remote DB can be costly. We can simplify and speed-up the process by effectively caching the set of pending transactions for use in the upcoming transactions dashboard. To do so, we will create a single table with denormalized data for the current pending transactions. As soon as a transaction is mined, it will be marked for removal from this DB after a short period (e.g. an hour).
Alternatively, we may opt for an in-memory data structure, completely omitting SQL usage.