DatriseAI-first ETL

Streak Oracle Database

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

How Datrise loads Streak into Oracle Database

Datrise syncs Streak's contacts, accounts, deals, activities, and lifecycle events 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

Streak: CRM for SMB teams managing pipeline, contacts, and customer activity.

Oracle Database: Enterprise RDBMS with advanced partitioning and HA.

How Streak entities map to Oracle Database

Streak entityOracle Database objectNotes
contactsstreak_contactsid PK · custom fields → JSON or CLOB columns
accountsstreak_accountsid PK · linked to streak_contacts
dealsstreak_dealsid PK · linked to streak_contacts
activitiesstreak_activitiesTIMESTAMP WITH TIME ZONE events

FAQ

How does Datrise handle Streak'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 Streak 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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