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Why is archiving data easier with SQL Server?
Archiving data becomes easier since each symbol is demarcated from others and reports generate faster for the user. Our data feeds solve a possible scaling problem and resolve the question of how to archive historic data that may need to be accessed by clients.
How to archive SQL Server data with scale in mind?
This designs for scale immediately. Data come from an application or ETL layer and enter a database designed for that partition of data, such as that year when the data originated or a partitioned key like a geographical area. Outside of moving the databases, no archiving is necessary.
How big should a SQL archive file be?
Data archiving processes should cause appreciable growth of the database log file. Clients should have the full week of historical data. The average daily historical data for one client grows to about 100,000 rows, and we have 40+ clients with 5 to 10 such tables.
Is there an automated process to archive big tables?
When I started to analyze the client’s historical data, I realized that there were no existing archive processes and the data was not archived, neither automatically nor manually. Some data goes back up to 5 years, resulting in a substantial increase of the database size.
How to automate the archiving process in SQL Server?
Automate the data archiving process – Setup rules with the users to be able to automate the archive process so it occurs regularly on a weekly, monthly or quarterly basis Once you understand how the data can be archived, now the technical decisions need to be made.
How does dynamic archiving of tables and data work?
Since most of the application is having some kind of mechanism to archive data like SQL stored procedures, statements, Database bound applications to do the archiving. I have seen having bigger and complex statements in SQL stored procedures to copy the data into archive tables based on some conditions, say created date etc.