DatriseAI-first ETL

WaiterAid to CSV Files Integration

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

How Datrise loads WaiterAid into CSV Files

Datrise syncs WaiterAid's bookings, guests, tables, restaurants, time slots, and booking statuses 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

WaiterAid: Restaurant reservations and table management.

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

How WaiterAid entities map to CSV Files

WaiterAid entityCSV Files objectNotes
bookingswaiteraid_bookingsid PK · custom fields → JSON-encoded strings for nested fields
guestswaiteraid_guestsid PK · linked to waiteraid_bookings
tableswaiteraid_tablesid PK · linked to waiteraid_bookings
restaurantswaiteraid_restaurantsid PK · linked to waiteraid_bookings

FAQ

How does Datrise handle WaiterAid'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 WaiterAid 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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