DatriseAI-first ETL

Vincle PostgreSQL

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

How Datrise loads Vincle into PostgreSQL

Datrise syncs Vincle'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

Vincle: European CRM for SMB and mid-market sales teams.

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

How Vincle entities map to PostgreSQL

Vincle entityPostgreSQL objectNotes
contactsvincle_contactsid PK · custom fields → jsonb columns
accountsvincle_accountsid PK · linked to vincle_contacts
dealsvincle_dealsid PK · linked to vincle_contacts
activitiesvincle_activitiestimestamptz events

FAQ

How does Datrise handle Vincle'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 Vincle 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

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