Overview
Google BigQuery is Google's petabyte-scale serverless data warehouse. The Automize BigQuery connector covers SQL queries, datasets, tables, jobs, and result retrieval.
- Regions: Per-region (us-central1, EU, asia-east1, etc.). Cross-region joins cost more.
- Plans: On-demand ($5/TB scanned) or flat-rate (commit slots/hour/month). Free tier: 1 TB queries/month, 10 GB storage.
Setting up the connection
Auth type: OAuth 2.0 (Authorization Code).
- GCP Console → Enable BigQuery API → Create OAuth client OR service account.
- Grant BigQuery Data Viewer + BigQuery Job User on the GCP project.
- In Automize → Settings → Connectors → BigQuery. Paste credentials + GCP project ID.
Find your credentials at https://console.cloud.google.com/apis/credentials.
Rate limits
100 concurrent queries per project. Per-user slot quota. Connector retries 429/503 with backoff.
Data model
Hierarchy:
Project ─── Datasets ─── Tables ─── Rows
└─ Jobs (Query, Load, Copy, Export)Available operations
7 operations available. Click any row to jump to its detail.
| Operation | Category | What it does |
|---|---|---|
| Get Query Results | General | Get results of a completed query job |
| Get Table | General | Get table schema/metadata |
| Insert Rows | General | Stream rows into a table |
| List Datasets | General | List all datasets in a project |
| List Jobs | General | List recent jobs |
| List Tables | General | List tables in a dataset |
| Run Query | General | Execute a SQL query |
Operations
Get Query Results
Get results of a completed query job
| Parameter | Required | Type | Description |
|---|---|---|---|
Project Id project_id | Yes | text | |
Job Id job_id | Yes | text |
Get Table
Get table schema/metadata
| Parameter | Required | Type | Description |
|---|---|---|---|
Project Id project_id | Yes | text | |
Dataset Id dataset_id | Yes | text | |
Table Id table_id | Yes | text |
Tips
- Returns table schema + size + partitioning + clustering.
Insert Rows
Stream rows into a table
| Parameter | Required | Type | Description |
|---|---|---|---|
Project Id project_id | Yes | text | |
Dataset Id dataset_id | Yes | text | |
Table Id table_id | Yes | text | |
Rows rows | Yes | text |
List Datasets
List all datasets in a project
| Parameter | Required | Type | Description |
|---|---|---|---|
Project Id project_id | Yes | text |
Tips
- Returns datasets in the project.
List Jobs
List recent jobs
| Parameter | Required | Type | Description |
|---|---|---|---|
Project Id project_id | Yes | text |
List Tables
List tables in a dataset
| Parameter | Required | Type | Description |
|---|---|---|---|
Project Id project_id | Yes | text | |
Dataset Id dataset_id | Yes | text |
Tips
- Per-dataset. Returns table metadata + schema.
Run Query
Execute a SQL query
| Parameter | Required | Type | Description |
|---|---|---|---|
Project Id project_id | Yes | text | |
Query query | Yes | text | |
Uselegacysql useLegacySql | Yes | text | |
Maxresults maxResults | Yes | text |
Tips
- SQL (StandardSQL by default). Returns job_id + results inline for small results.
- useLegacySql=false for StandardSQL (default). useQueryCache=true reuses recent identical query results.
FAQ
- On-demand vs flat-rate?
- On-demand: pay per TB scanned. Flat-rate: pre-commit slots. Flat-rate cheaper if you have steady high volume; on-demand for spiky.
- Why is my query slow?
- Common culprits: SELECT * (scans all columns), no partition filter on partitioned tables, JOIN order, no clustering.