DatriseAI-first ETL

Fastbill to CSV Files Integration

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

How Datrise loads Fastbill into CSV Files

Datrise syncs Fastbill's invoices, customers, line items, payments, expenses, and recurring invoices 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

Fastbill: Invoicing and accounting for small businesses.

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

How Fastbill entities map to CSV Files

Fastbill entityCSV Files objectNotes
invoicesfastbill_invoicesid PK · custom fields → JSON-encoded strings for nested fields
customersfastbill_customersid PK · linked to fastbill_invoices
line itemsfastbill_line_itemsid PK · linked to fastbill_invoices
paymentsfastbill_paymentsid PK · linked to fastbill_invoices

FAQ

How does Datrise handle Fastbill'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 Fastbill 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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