DatriseAI-first ETL

Selligent to Amazon Redshift Integration

AI-first ETL from Selligent into Amazon Redshift. Governed entities, incremental sync, typed landing tables.

How Datrise loads Selligent into Amazon Redshift

Datrise syncs Selligent's contacts, journeys, campaigns, message events, lists, and real-time triggers into Amazon Redshift as a typed table per source entity. Flexible or custom fields land in SUPER columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMPTZ.

Sync is incremental: Datrise uses COPY from staged files, then a delete-and-insert merge on stable id, so re-runs update only what changed. A DISTKEY on the join id and a SORTKEY on the load timestamp. Redshift performance hinges on dist/sort keys, so Datrise picks them from your entity ids and sync timestamps rather than defaulting to EVEN distribution.

Ideal for AWS-native warehouses already using the Redshift ecosystem.

Endpoints

Selligent: Enterprise cross-channel campaigns with real-time triggers.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Selligent entities map to Amazon Redshift

Selligent entityAmazon Redshift objectNotes
contactsselligent_contactsid PK · custom fields → SUPER columns
journeysselligent_journeysid PK · linked to selligent_contacts
campaignsselligent_campaignsid PK · linked to selligent_contacts
message eventsselligent_message_eventsTIMESTAMPTZ events

FAQ

How does Datrise handle Selligent's custom fields in Amazon Redshift?

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

How does the Selligent to Amazon Redshift sync stay up to date?

It runs incrementally — Datrise uses COPY from staged files, then a delete-and-insert merge on stable id.

Related pipelines

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