DatriseAI-first ETL

Braze to Oracle Database Integration

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

How Datrise loads Braze into Oracle Database

Datrise syncs Braze's users, campaigns, canvases, message events, segments, and custom attributes 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

Braze: Cross-channel customer engagement platform.

Oracle Database: Enterprise RDBMS with advanced partitioning and HA.

How Braze entities map to Oracle Database

Braze entityOracle Database objectNotes
usersbraze_usersid PK · custom fields → JSON or CLOB columns
campaignsbraze_campaignsid PK · linked to braze_users
canvasesbraze_canvasesid PK · linked to braze_users
message eventsbraze_message_eventsTIMESTAMP WITH TIME ZONE events

FAQ

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

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

Related pipelines

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