DatriseAI-first ETL

PipeRun PostgreSQL

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

How Datrise loads PipeRun into PostgreSQL

Datrise syncs PipeRun'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

PipeRun: CRM widely used in Latin America for sales pipeline and customer ops.

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

How PipeRun entities map to PostgreSQL

PipeRun entityPostgreSQL objectNotes
contactspiperun_contactsid PK · custom fields → jsonb columns
accountspiperun_accountsid PK · linked to piperun_contacts
dealspiperun_dealsid PK · linked to piperun_contacts
activitiespiperun_activitiestimestamptz events

FAQ

How does Datrise handle PipeRun'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 PipeRun 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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