DatriseAI-first ETL

Oracle Db Mode

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

How Datrise loads Oracle Db into Mode

Datrise syncs Oracle Db's records, events, and configuration objects into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.

Ideal for SQL-first analysis with Python and R notebooks.

Endpoints

Oracle Db: SaaS or API data source for analytics and warehouse sync.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How Oracle Db entities map to Mode

Oracle Db entityMode objectNotes
recordsoracle_db_recordsid PK · custom fields → flattened columns for SQL and notebooks
eventsoracle_db_eventstemporal columns events
configuration objectsoracle_db_configuration_objectsid PK · linked to oracle_db_records

FAQ

How does Datrise handle Oracle Db's custom fields in Mode?

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

How does the Oracle Db to Mode sync stay up to date?

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

Related pipelines

Early access

Connect Oracle Db to Mode 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.