DatriseAI-first ETL

Oracle Database to Tableau Integration

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

How Datrise loads Oracle Database into Tableau

Datrise syncs Oracle Database's tables, rows, schemas, indexes, sequences, and redo log changes into Tableau as warehouse tables or a refreshed .hyper extract. Flexible or custom fields land in flattened columns for Tableau fields, and timestamps such as created, updated, and status changes are typed as date/datetime fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind a live connection or extract, so re-runs update only what changed. Date-partitioned facts to keep extract refresh quick. Tableau .hyper extracts snapshot data, so Datrise keeps the source tables incremental and lets you choose live vs extract.

Ideal for visual analytics and dashboards in Tableau.

Endpoints

Oracle Database: Oracle Database for enterprise transactional workloads.

Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.

How Oracle Database entities map to Tableau

Oracle Database entityTableau objectNotes
tablesoracle_db_tablesid PK · custom fields → flattened columns for Tableau 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 Tableau?

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

How does the Oracle Database to Tableau sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind a live connection or extract.

Related pipelines

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Connect Oracle Database to Tableau the easy way

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