- Is this your first time deploying Airbyte?: No
- Memory / Disk: you can use something like 4Gb / 1 Tb
- Deployment: Kube
- Airbyte Version: 40.15
- Source name/version: Postgres 1.0.19 and SQL Server 0.4.23
- Destination name/version: Snowflake 0.4.38
- Step: Sync/read
Both the Postgres and SQL Server source convert all date/time related datatypes into strings, currently.
First question: why was this done this way?
More importantly: how do we best work around this? Simple solution would be an additional transform (whether in Airbyte/DBT or after the fact); however this is just inefficient (additional compute cost, time, and storage space). I was wondering if there’s maybe an easy way to inject our own datatypes into the base normalization maybe, while still maintaining the rest of the built-in normalization logic (IE deduping), and ensuring any future changes to normalization are still propagated. Or maybe another way entirely that I’m not aware of?