DatriseAI-first ETL

Brevo to Amazon Redshift Integration

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

How Datrise loads Brevo into Amazon Redshift

Datrise syncs Brevo's contacts, lists, campaigns, transactional emails, deals, and email events 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

Brevo: Email, SMS, and CRM for small business lifecycle marketing.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Brevo entities map to Amazon Redshift

Brevo entityAmazon Redshift objectNotes
contactsbrevo_contactsid PK · custom fields → SUPER columns
listsbrevo_listsid PK · linked to brevo_contacts
campaignsbrevo_campaignsid PK · linked to brevo_contacts
transactional emailsbrevo_transactional_emailsid PK · linked to brevo_contacts

FAQ

How does Datrise handle Brevo'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 Brevo 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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