DatriseAI-first ETL

Delighted Amazon Redshift

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

How Datrise loads Delighted into Amazon Redshift

Datrise syncs Delighted's surveys, responses, scores, and follow-up workflows 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

Delighted: NPS and micro-survey feedback platform.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Delighted entities map to Amazon Redshift

Delighted entityAmazon Redshift objectNotes
surveysdelighted_surveysid PK · custom fields → SUPER columns
responsesdelighted_responsesid PK · linked to delighted_surveys
scoresdelighted_scoresid PK · linked to delighted_surveys
follow-up workflowsdelighted_follow_up_workflowsid PK · linked to delighted_surveys

FAQ

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

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