DatriseAI-first ETL

Bronto to Amazon Redshift Integration

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

How Datrise loads Bronto into Amazon Redshift

Datrise syncs Bronto's contacts, deliveries, campaigns, orders, 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

Bronto: Email marketing automation for commerce.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Bronto entities map to Amazon Redshift

Bronto entityAmazon Redshift objectNotes
contactsbronto_contactsid PK · custom fields → SUPER columns
deliveriesbronto_deliveriesid PK · linked to bronto_contacts
campaignsbronto_campaignsid PK · linked to bronto_contacts
ordersbronto_ordersid PK · linked to bronto_contacts

FAQ

How does Datrise handle Bronto'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 Bronto 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

Connect Bronto to Amazon Redshift the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.