Google Cloud Storage to Redash Integration

How Datrise loads Google Cloud Storage into Redash

Datrise syncs Google Cloud Storage's buckets, objects, prefixes, object metadata, generations, and storage classes into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.

Ideal for lightweight, query-driven dashboards.

Endpoints

Google Cloud Storage: Object storage for files and data lake exports on GCP.

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Google Cloud Storage entities map to Redash

Google Cloud Storage entity	Redash object	Notes
buckets	`google_cloud_storage_f_buckets`	id PK · custom fields → flattened columns for query results
objects	`google_cloud_storage_f_objects`	id PK · linked to google_cloud_storage_f_buckets
prefixes	`google_cloud_storage_f_prefixes`	id PK · linked to google_cloud_storage_f_buckets
object metadata	`google_cloud_storage_f_object_metadata`	id PK · linked to google_cloud_storage_f_buckets

FAQ

How does Datrise handle Google Cloud Storage's custom fields in Redash?

Flexible values are stored as flattened columns for query results, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Redash types.

How does the Google Cloud Storage to Redash sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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