GoCardless to Mode Integration
AI-first ETL from GoCardless into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads GoCardless into Mode
Datrise syncs GoCardless's payments, customers, mandates, subscriptions, payouts, and refunds into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.
Ideal for SQL-first analysis with Python and R notebooks.
Endpoints
GoCardless: Bank debit collection and recurring payments.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How GoCardless entities map to Mode
| GoCardless entity | Mode object | Notes |
|---|---|---|
| payments | gocardless_payments | id PK · custom fields → flattened columns for SQL and notebooks |
| 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 Mode?
Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.
How does the GoCardless to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
More destinations for GoCardless
Early access
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