What causes Database Error: BigQuery Quota Exceeded?

Too many dbt models running in parallel exceeding the BigQuery concurrent query quota (default 300 per project). dbt full-refresh or large incremental run processing more bytes than the project's daily quota allows. Multiple dbt runs executing simultaneously against the same project. BigQuery slot quota exhausted for on-demand pricing, causing query queuing that times out. BigQuery Admin API quota exceeded by dbt's metadata operations (list tables, get schema)

How do I fix Database Error: BigQuery Quota Exceeded?

Reduce dbt parallelism: set `threads: 4` (or lower) in profiles.yml. Add `--threads 2` to the dbt run command for large full-refresh runs. Request a quota increase in Google Cloud Console: APIs & Services → Quotas. Use dbt's `--select` flag to run only the changed models rather than all models. Implement BigQuery slot reservations to move from on-demand to capacity-based pricing for predictable workloads. Schedule large dbt runs during off-peak hours to avoid concurrent quota contention

High severityinfrastructure

Power BI Refresh Error:
Database Error: BigQuery Quota Exceeded

What does this error mean?

A dbt run against BigQuery failed because a Google Cloud quota limit was reached — most commonly the concurrent queries per project quota or the daily bytes processed limit.

Common causes

1Too many dbt models running in parallel exceeding the BigQuery concurrent query quota (default 300 per project)
2dbt full-refresh or large incremental run processing more bytes than the project's daily quota allows
3Multiple dbt runs executing simultaneously against the same project
4BigQuery slot quota exhausted for on-demand pricing, causing query queuing that times out
5BigQuery Admin API quota exceeded by dbt's metadata operations (list tables, get schema)

How to fix it

1Reduce dbt parallelism: set `threads: 4` (or lower) in profiles.yml
2Add `--threads 2` to the dbt run command for large full-refresh runs
3Request a quota increase in Google Cloud Console: APIs & Services → Quotas
4Use dbt's `--select` flag to run only the changed models rather than all models
5Implement BigQuery slot reservations to move from on-demand to capacity-based pricing for predictable workloads
6Schedule large dbt runs during off-peak hours to avoid concurrent quota contention

Frequently asked questions

How do I check my current BigQuery quota usage?

In Google Cloud Console, go to IAM & Admin → Quotas and filter by BigQuery. You can also query `INFORMATION_SCHEMA.JOBS_BY_PROJECT` in BigQuery to see concurrent job counts.