DatriseAI-first ETL

Oracle Database to Mode Integration

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

How Datrise loads Oracle Database into Mode

Datrise syncs Oracle Database's tables, rows, schemas, indexes, sequences, and redo log changes 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 Database: Oracle Database for enterprise transactional workloads.

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

How Oracle Database entities map to Mode

Oracle Database entityMode objectNotes
tablesoracle_db_tablesid PK · custom fields → flattened columns for SQL and notebooks
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 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 Database to Mode sync stay up to date?

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

Related pipelines

Early access

Connect Oracle Database to Mode the easy way

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