2. Modify the application to write to the target database

How exactly to do this is dependent on the language that your application is written in, and on how exactly your ingestion and application function. In the simplest case, you simply execute two inserts in parallel. In the general case, you must think about how to handle the failure to write to either the source or target database, and what mechanism you want to or can build to recover from such a failure.

Should your time-series data have foreign-key references into a plain table, you must ensure that your application correctly maintains the foreign key relations. If the referenced column is a *SERIAL type, the same row inserted into the source and target may not obtain the same autogenerated id. If this happens, the data backfilled from the source to the target is internally inconsistent. In the best case it causes a foreign key violation, in the worst case, the foreign key constraint is maintained, but the data references the wrong foreign key. To avoid these issues, best practice is to follow [live migration].

You may also want to execute the same read queries on the source and target database to evaluate the correctness and performance of the results which the queries deliver. Bear in mind that the target database spends a certain amount of time without all data being present, so you should expect that the results are not the same for some period (potentially a number of days).

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Operation system	Version
Debian	13 Trixe, 12 Bookworm, 11 Bullseye
Ubuntu	24.04 Noble Numbat, 22.04 LTS Jammy Jellyfish
Red Hat Enterprise	Linux 9, Linux 8
Fedora	Fedora 35, Fedora 34, Fedora 33
Rocky Linux	Rocky Linux 9 (x86_64), Rocky Linux 8
ArchLinux (community-supported)	Check the [available packages][archlinux-packages]

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