DatriseAI-first ETL

ActiveCampaign Amazon Redshift

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

How Datrise loads ActiveCampaign into Amazon Redshift

Datrise syncs ActiveCampaign's contacts, automations, campaigns, and sales pipeline updates 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

ActiveCampaign: CRM plus marketing automation and journeys.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How ActiveCampaign entities map to Amazon Redshift

ActiveCampaign entityAmazon Redshift objectNotes
contactsactivecampaign_contactsid PK · custom fields → SUPER columns
automationsactivecampaign_automationsid PK · linked to activecampaign_contacts
campaignsactivecampaign_campaignsid PK · linked to activecampaign_contacts
sales pipeline updatesactivecampaign_sales_pipeline_updatesid PK · linked to activecampaign_contacts

FAQ

How does Datrise handle ActiveCampaign'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 ActiveCampaign 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

Early access

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