DatriseAI-first ETL

Delighted PostgreSQL

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

How Datrise loads Delighted into PostgreSQL

Datrise syncs Delighted's surveys, responses, scores, and follow-up workflows into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

Delighted: NPS and micro-survey feedback platform.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Delighted entities map to PostgreSQL

Delighted entityPostgreSQL objectNotes
surveysdelighted_surveysid PK · custom fields → jsonb 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 PostgreSQL?

Flexible values are stored as jsonb columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native PostgreSQL types.

How does the Delighted to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

Early access

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