DatriseAI-first ETL

Responsys to PostgreSQL Integration

AI-first ETL from Responsys into PostgreSQL. Governed entities, incremental sync, typed landing tables.

How Datrise loads Responsys into PostgreSQL

Datrise syncs Responsys's contacts, campaigns, launches, message events, lists, and profile extensions into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

Responsys: Enterprise cross-channel campaign orchestration.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Responsys entities map to PostgreSQL

Responsys entityPostgreSQL objectNotes
contactsresponsys_contactsid PK · custom fields → jsonb columns
campaignsresponsys_campaignsid PK · linked to responsys_contacts
launchesresponsys_launchesid PK · linked to responsys_contacts
message eventsresponsys_message_eventstimestamptz events

FAQ

How does Datrise handle Responsys's custom fields in PostgreSQL?

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

How does the Responsys to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

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