We are using Django with its ORM in connection with an underlying PostgreSQL database and want to extend the data model and technology stack to store massive amounts of time series data (~5 million entries per day
onwards).
The closest questions I found were this and this which propose to combine Django with databases such as TimescaleDB
or InfluxDB
. But his creates parallel structures to Django's builtin ORM and thus does not seem to be straightforward.
How can we handle large amounts of time series data while preserving or staying really close to Django's ORM?
Any hints on proven technology stacks and implementation patterns are welcome!