GoCardless to DuckDB Integration
AI-first ETL from GoCardless into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads GoCardless into DuckDB
Datrise syncs GoCardless's payments, customers, mandates, subscriptions, payouts, and refunds into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.
Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.
Ideal for local and notebook analytics without standing up a server.
Endpoints
GoCardless: Bank debit collection and recurring payments.
DuckDB: In-process analytics database for fast local OLAP.
How GoCardless entities map to DuckDB
| GoCardless entity | DuckDB object | Notes |
|---|---|---|
| payments | gocardless_payments | id PK · custom fields → JSON or STRUCT columns |
| customers | gocardless_customers | id PK · linked to gocardless_payments |
| mandates | gocardless_mandates | id PK · linked to gocardless_payments |
| subscriptions | gocardless_subscriptions | id PK · linked to gocardless_payments |
FAQ
How does Datrise handle GoCardless's custom fields in DuckDB?
Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.
How does the GoCardless to DuckDB sync stay up to date?
It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.
Related pipelines
More destinations for GoCardless
Early access
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