DatriseAI-first ETL

Recurly CSV Files

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

How Datrise loads Recurly into CSV Files

Datrise syncs Recurly's subscriptions, invoices, plans, transactions, and dunning events 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

Recurly: Subscription management and recurring billing platform.

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

How Recurly entities map to CSV Files

Recurly entityCSV Files objectNotes
subscriptionsrecurly_subscriptionsid PK · custom fields → JSON-encoded strings for nested fields
invoicesrecurly_invoicesid PK · linked to recurly_subscriptions
plansrecurly_plansid PK · linked to recurly_subscriptions
transactionsrecurly_transactionsid PK · linked to recurly_subscriptions

FAQ

How does Datrise handle Recurly'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 Recurly 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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