DatriseAI-first ETL

Google Cloud SQL MicroStrategy

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

How Datrise loads Google Cloud SQL into MicroStrategy

Datrise syncs Google Cloud SQL's records, events, and configuration objects into MicroStrategy as warehouse tables for MicroStrategy's schema objects. 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 warehouse tables behind attributes and metrics, so re-runs update only what changed. Date-partitioned facts. MicroStrategy maps attributes to columns, so Datrise lands stable keys and names so metrics don't break.

Ideal for large-scale enterprise reporting and governance.

Endpoints

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

MicroStrategy: Enterprise BI with dossiers, governed metrics, and mobility.

How Google Cloud SQL entities map to MicroStrategy

Google Cloud SQL entityMicroStrategy 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 MicroStrategy?

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 MicroStrategy types.

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

It runs incrementally — Datrise uses incremental refresh of the warehouse tables behind attributes and metrics.

Related pipelines

Early access

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