DatriseAI-first ETL

Google Cloud SQL Yellowfin

AI-first ETL from Google Cloud SQL into Yellowfin. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Cloud SQL into Yellowfin

Datrise syncs Google Cloud SQL's records, events, and configuration objects into Yellowfin as warehouse tables Yellowfin builds views on. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. Yellowfin views reference columns by name, so Datrise lands stable, well-typed columns to keep reports valid.

Ideal for dashboards with automated data storytelling.

Endpoints

Google Cloud SQL: SaaS or API data source for analytics and warehouse sync.

Yellowfin: BI suite with dashboards, automated insights, and data storytelling.

How Google Cloud SQL entities map to Yellowfin

Google Cloud SQL entityYellowfin objectNotes
recordsgoogle_cloud_sql_recordsid PK · custom fields → flattened columns
eventsgoogle_cloud_sql_eventsdate/time dimensions events
configuration objectsgoogle_cloud_sql_configuration_objectsid PK · linked to google_cloud_sql_records

FAQ

How does Datrise handle Google Cloud SQL's custom fields in Yellowfin?

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

How does the Google Cloud SQL to Yellowfin sync stay up to date?

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

Related pipelines

Early access

Connect Google Cloud SQL to Yellowfin the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.