DatriseAI-first ETL

Stripe CSV Files

AI-first ETL from Stripe into CSV Files. Governed entities, incremental sync, typed landing tables.

How Datrise loads Stripe into CSV Files

Datrise syncs Stripe's charges, customers, subscriptions, invoices, and balance transactions into CSV Files as one CSV per source entity. Flexible or custom fields land in JSON-encoded strings for nested fields, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.

Sync is incremental: Datrise uses writes a fresh, fully-typed CSV per entity each run, so re-runs update only what changed. Optional date-suffixed files for change tracking. CSV has no types, so Datrise emits a companion schema and quotes/escapes consistently so downstream loaders don't misparse commas and newlines.

Ideal for portable hand-off into any tool that ingests delimited files.

Endpoints

Stripe: Payments infrastructure for charges, subscriptions, and payouts.

CSV Files: Flat-file destination for exports and lightweight data sharing.

How Stripe entities map to CSV Files

Stripe entityCSV Files objectNotes
chargesstripe_chargesid PK · custom fields → JSON-encoded strings for nested fields
customersstripe_customersid PK · linked to stripe_charges
subscriptionsstripe_subscriptionsid PK · linked to stripe_charges
invoicesstripe_invoicesid PK · linked to stripe_charges

FAQ

How does Datrise handle Stripe's custom fields in CSV Files?

Flexible values are stored as JSON-encoded strings for nested fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native CSV Files types.

How does the Stripe to CSV Files sync stay up to date?

It runs incrementally — Datrise uses writes a fresh, fully-typed CSV per entity each run.

Related pipelines

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