On Sun, Mar 3, 2024 at 2:06 PM yudhi s <learnerdatabas...@gmail.com> wrote:
> Hello, > We have an application in which the tables will have approx ~200 columns > in some of the big transaction tables when we will be serving all the > business use cases. Currently it has ~100 columns to serve current business > use cases to start with. As the team is following an agile approach , the > attributes will be added gradually with each future release. But the > concern is, the transaction tables will be holding billions of rows ( > because of historical data migration from start) and will be range > partitioned and each of those partitions can be as big as ~100GB and full > table size can be in multiple Terabytes. > > So our concern was , as the column addition using the traditional "Alter > table" command in postgres looks to be a full table rewrite , it’s going to > take a lot of time and resources with each of such releases for these big > transaction tables. So what is the way to handle such scenarios and do > these column additions in quick time with no/minimal downtime? > Normalizing the database design completely eliminates the problem of any need to rewrite a table, since new attributes are added as new rows in a different table.
