GoCardless to Apache Superset Integration
AI-first ETL from GoCardless into Apache Superset. Governed entities, incremental sync, typed landing tables.
How Datrise loads GoCardless into Apache Superset
Datrise syncs GoCardless's payments, customers, mandates, subscriptions, payouts, and refunds into Apache Superset as governed SQL tables Superset queries directly. Flexible or custom fields land in flattened columns for the explore UI, and timestamps such as created, updated, and status changes are typed as temporal columns for time-series charts.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned tables to keep dashboards responsive. Superset charts run live SQL, so Datrise lands query-friendly, indexed tables rather than wide raw payloads.
Ideal for open-source dashboards over your own database.
Endpoints
GoCardless: Bank debit collection and recurring payments.
Apache Superset: Open-source BI for SQL exploration, charts, and dashboard publishing.
How GoCardless entities map to Apache Superset
| GoCardless entity | Apache Superset object | Notes |
|---|---|---|
| payments | gocardless_payments | id PK · custom fields → flattened columns for the explore UI |
| 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 Apache Superset?
Flexible values are stored as flattened columns for the explore UI, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Apache Superset types.
How does the GoCardless to Apache Superset sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
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Early access
Connect GoCardless to Apache Superset the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.