DatriseAI-first ETL

Microsoft Dataverse Oracle Database

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

How Datrise loads Microsoft Dataverse into Oracle Database

Datrise syncs Microsoft Dataverse'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

Microsoft Dataverse: SaaS or API data source for analytics and warehouse sync.

Oracle Database: Enterprise RDBMS with advanced partitioning and HA.

How Microsoft Dataverse entities map to Oracle Database

Microsoft Dataverse entityOracle Database objectNotes
recordsmicrosoft_dataverse_recordsid PK · custom fields → JSON or CLOB columns
eventsmicrosoft_dataverse_eventsTIMESTAMP WITH TIME ZONE events
configuration objectsmicrosoft_dataverse_configuration_objectsid PK · linked to microsoft_dataverse_records

FAQ

How does Datrise handle Microsoft Dataverse'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 Microsoft Dataverse to Oracle Database sync stay up to date?

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

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