You can do your own forecasting in SQL with Python or R. Depending which database you use, there will probably be some kind of integration. Postgres has PL/R and PL/Python.
I recently tried this in a Google tutorial, it was very nice, but I was surprised to learn in the same tutorial that Google Cloud AutoML provides better results than BigQuery ML.
Check out the statistical functions baked into Snowflake SQL. We've got a PL/SQL script that forecasts sales volume with seasonality, using a modified ARIMA approach. We're also turning this approach loose on our own data pipeline to trigger alerts on abnormal row counts.