DatriseAI-first ETL

Salesforce Marketing Cloud to Amazon Redshift Integration

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

How Datrise loads Salesforce Marketing Cloud into Amazon Redshift

Datrise syncs Salesforce Marketing Cloud's subscribers, data extensions, journeys, sends, email events, and lists 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

Salesforce Marketing Cloud: Enterprise email, journeys, and cross-channel messaging.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Salesforce Marketing Cloud entities map to Amazon Redshift

Salesforce Marketing Cloud entityAmazon Redshift objectNotes
subscriberssalesforce_marketing_cloud_subscribersid PK · custom fields → SUPER columns
data extensionssalesforce_marketing_cloud_data_extensionsid PK · linked to salesforce_marketing_cloud_subscribers
journeyssalesforce_marketing_cloud_journeysid PK · linked to salesforce_marketing_cloud_subscribers
sendssalesforce_marketing_cloud_sendsid PK · linked to salesforce_marketing_cloud_subscribers

FAQ

How does Datrise handle Salesforce Marketing Cloud'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 Salesforce Marketing Cloud 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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