DatriseAI-first ETL

Mailchimp Amazon Redshift

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

How Datrise loads Mailchimp into Amazon Redshift

Datrise syncs Mailchimp's audiences, campaigns, automations, subscribers, and engagement metrics 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

Mailchimp: Email marketing platform with audiences and campaign analytics.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Mailchimp entities map to Amazon Redshift

Mailchimp entityAmazon Redshift objectNotes
audiencesmailchimp_audiencesid PK · custom fields → SUPER columns
campaignsmailchimp_campaignsid PK · linked to mailchimp_audiences
automationsmailchimp_automationsid PK · linked to mailchimp_audiences
subscribersmailchimp_subscribersid PK · linked to mailchimp_audiences

FAQ

How does Datrise handle Mailchimp'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 Mailchimp 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.

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Early access

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