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BigQuery

Overview

Google BigQuery is a fully managed, serverless data warehouse designed for large-scale analytics. It supports standard SQL, nested and repeated fields, partitioned tables, materialized views, and integrates with the broader Google Cloud ecosystem. BigQuery separates storage from compute, scaling automatically to petabyte-scale workloads.

Driver

Connection fields

Field Description
Project ID The GCP project ID that owns the BigQuery datasets (e.g. my-gcp-project).
Credentials File Path to a service account JSON key file. Leave empty to use Application Default Credentials.
Options Additional parameters as key1=val1&key2=val2.

Authentication

BigQuery supports two authentication methods. Arris tries them in order:

Service account key file — provide the path to a JSON key file downloaded from the GCP Console. The service account must have the BigQuery Data Viewer and BigQuery Job User roles at minimum. For write operations (staged edits), add BigQuery Data Editor.

Application Default Credentials (ADC) — if no credentials file is provided, Arris uses the GOOGLE_APPLICATION_CREDENTIALS environment variable or the default credentials configured via gcloud auth application-default login.

All traffic to BigQuery goes over HTTPS. There is no option to disable TLS, and no SSH tunnel is needed since BigQuery is a cloud-only service.

Schema browser

Once connected, Arris lists all datasets in the project and fetches table metadata from INFORMATION_SCHEMA. The schema tree is organized as Project → Dataset → objects.

Double-click any table or view to open it in browse mode.

Supported SQL commands

Command Notes
SELECT Query data with WHERE filters, JOINs, aggregates, and window functions.
INSERT Insert rows via DML statements.
UPDATE Update rows via DML statements.
DELETE Delete rows via DML statements.
CREATE / DROP Create and drop tables, views, and other schema objects.