DatriseAI-first ETL

Klaviyo Amazon Redshift

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

How Datrise loads Klaviyo into Amazon Redshift

Datrise syncs Klaviyo's profiles, segments, flows, campaigns, and attributed revenue 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

Klaviyo: E-commerce marketing automation with email and SMS.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Klaviyo entities map to Amazon Redshift

Klaviyo entityAmazon Redshift objectNotes
profilesklaviyo_profilesid PK · custom fields → SUPER columns
segmentsklaviyo_segmentsid PK · linked to klaviyo_profiles
flowsklaviyo_flowsid PK · linked to klaviyo_profiles
campaignsklaviyo_campaignsid PK · linked to klaviyo_profiles

FAQ

How does Datrise handle Klaviyo'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 Klaviyo 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 Klaviyo to Amazon Redshift the easy way

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