DatriseAI-first ETL

Google Cloud SQL Oracle Database

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

How Datrise loads Google Cloud SQL into Oracle Database

Datrise syncs Google Cloud SQL's records, events, and configuration objects into Oracle Database as a typed table per source entity. Flexible or custom fields land in JSON or CLOB columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses a watermark on updated-at, applied with MERGE INTO, so re-runs update only what changed. Optional range partitioning by load date. Oracle treats an empty string as NULL, so Datrise distinguishes blank source values from missing ones during load.

Ideal for enterprise data teams consolidating CRM data into an Oracle warehouse.

Endpoints

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

Oracle Database: Enterprise RDBMS with advanced partitioning and HA.

How Google Cloud SQL entities map to Oracle Database

Google Cloud SQL entityOracle Database objectNotes
recordsgoogle_cloud_sql_recordsid PK · custom fields → JSON or CLOB columns
eventsgoogle_cloud_sql_eventsTIMESTAMP WITH TIME ZONE 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 Oracle Database?

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

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

It runs incrementally — Datrise uses a watermark on updated-at, applied with MERGE INTO.

Related pipelines

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