DatriseAI-first ETL

Clay PostgreSQL

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

How Datrise loads Clay into PostgreSQL

Datrise syncs Clay's contacts, accounts, deals, activities, and lifecycle events into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

Clay: AI-native CRM for relationship data, enrichment, and workflow automation.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Clay entities map to PostgreSQL

Clay entityPostgreSQL objectNotes
contactsclay_contactsid PK · custom fields → jsonb columns
accountsclay_accountsid PK · linked to clay_contacts
dealsclay_dealsid PK · linked to clay_contacts
activitiesclay_activitiestimestamptz events

FAQ

How does Datrise handle Clay's custom fields in PostgreSQL?

Flexible values are stored as jsonb columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native PostgreSQL types.

How does the Clay to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

Early access

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