DatriseAI-first ETL

Clay to CSV Files Integration

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

How Datrise loads Clay into CSV Files

Datrise syncs Clay's tables, rows, enrichment runs, waterfalls, data sources, and exported lists 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

Clay: Data enrichment tables that build outbound lists.

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

How Clay entities map to CSV Files

Clay entityCSV Files objectNotes
tablesclay_tablesid PK · custom fields → JSON-encoded strings for nested fields
rowsclay_rowsid PK · linked to clay_tables
enrichment runsclay_enrichment_runsid PK · linked to clay_tables
waterfallsclay_waterfallsid PK · linked to clay_tables

FAQ

How does Datrise handle Clay'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 Clay 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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