DatriseAI-first ETL

Merge to CSV Files Integration

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

How Datrise loads Merge into CSV Files

Datrise syncs Merge's linked accounts, employees, candidates, contacts, invoices, and sync 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

Merge: Unified API across HR, CRM, and accounting tools.

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

How Merge entities map to CSV Files

Merge entityCSV Files objectNotes
linked accountsmerge_linked_accountsid PK · custom fields → JSON-encoded strings for nested fields
employeesmerge_employeesid PK · linked to merge_linked_accounts
candidatesmerge_candidatesid PK · linked to merge_linked_accounts
contactsmerge_contactsid PK · linked to merge_linked_accounts

FAQ

How does Datrise handle Merge'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 Merge 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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