We would have date specific trading data for about 10M trades - each day's data comprising ~1T data in different collections like market,trade,settlements etc.
Since we would not need more than 3 days data at any point of time - intention is to delete all data pertaining to T-3 or more.
There would be 2 possible options:
1.Each trading day being represented as a separate database - with the standard set of collections viz marketdata,trade,settlementdata in each database
2.Every collection being appended with the date viz marketdata_10032019,marketdata_10042019 etc
The first option seems better as:
1. much cleaner in terms of maintenance - just dropping the obsolete databases,rather than scanning collections by name.
2. Dynamic collection names as in second option puts severe restrictions in aggregation possibilities - mongo aggregation does not support dynamic names.
Would appreciate further views - based on performance,concurrency,scalability,clustering/sharding,maintenance etc
All earlier questions do not address the used case of maintaining a second-level logically aggregated grouping of collections based on date