Google Cloud Storage to ThoughtSpot Integration

How Datrise loads Google Cloud Storage into ThoughtSpot

Datrise syncs Google Cloud Storage's buckets, objects, prefixes, object metadata, generations, and storage classes into ThoughtSpot as warehouse tables ThoughtSpot indexes for search. Flexible or custom fields land in flattened columns for searchable fields, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the indexed tables, so re-runs update only what changed. Date-partitioned facts for live-query performance. ThoughtSpot search relies on clear names and relationships, so Datrise lands well-named, joinable tables.

Ideal for natural-language search analytics over a warehouse.

Endpoints

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

ThoughtSpot: Search-driven analytics with AI-assisted insights on warehouse data.

How Google Cloud Storage entities map to ThoughtSpot

Google Cloud Storage entity	ThoughtSpot object	Notes
buckets	`google_cloud_storage_f_buckets`	id PK · custom fields → flattened columns for searchable fields
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 ThoughtSpot?

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

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

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

Related pipelines

Early access

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