DatriseAI-first ETL

GoCardless to PostgreSQL Integration

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

How Datrise loads GoCardless into PostgreSQL

Datrise syncs GoCardless's payments, customers, mandates, subscriptions, payouts, and refunds 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

GoCardless: Bank debit collection and recurring payments.

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

How GoCardless entities map to PostgreSQL

GoCardless entityPostgreSQL objectNotes
paymentsgocardless_paymentsid PK · custom fields → jsonb columns
customersgocardless_customersid PK · linked to gocardless_payments
mandatesgocardless_mandatesid PK · linked to gocardless_payments
subscriptionsgocardless_subscriptionsid PK · linked to gocardless_payments

FAQ

How does Datrise handle GoCardless'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 GoCardless 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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