DatriseAI-first ETL

Oracle Database to Looker Studio Integration

AI-first ETL from Oracle Database into Looker Studio. Governed entities, incremental sync, typed landing tables.

How Datrise loads Oracle Database into Looker Studio

Datrise syncs Oracle Database's tables, rows, schemas, indexes, sequences, and redo log changes into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

Oracle Database: Oracle Database for enterprise transactional workloads.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How Oracle Database entities map to Looker Studio

Oracle Database entityLooker Studio objectNotes
tablesoracle_db_tablesid PK · custom fields → flattened columns for chart fields
rowsoracle_db_rowsid PK · linked to oracle_db_tables
schemasoracle_db_schemasid PK · linked to oracle_db_tables
indexesoracle_db_indexesid PK · linked to oracle_db_tables

FAQ

How does Datrise handle Oracle Database's custom fields in Looker Studio?

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

How does the Oracle Database to Looker Studio sync stay up to date?

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

Related pipelines

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