That's an interesting question. Behind the scenes, BigQuery uses an auto Arima model to extrapolate the trend of the time series after deseasonalizing them (https://cloud.google.com/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-create-time-series). I would say that the complexity of the pipeline makes it slower (also our implementations use numba which speeds up the fitting time).