DatriseAI-first ETL

Impartner Neon

AI-first ETL from Impartner into Neon. Governed entities, incremental sync, typed landing tables.

How Datrise loads Impartner into Neon

Datrise syncs Impartner's contacts, accounts, deals, activities, and lifecycle events into Neon 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 updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative partitioning by load date. Neon separates compute from storage, so Datrise batches writes to keep autoscaling compute from cold-starting on every small change.

Ideal for serverless Postgres workloads that scale to zero between syncs.

Endpoints

Impartner: Partner relationship management for channels and co-sell motions.

Neon: Serverless Postgres destination with branching and autoscaling.

How Impartner entities map to Neon

Impartner entityNeon objectNotes
contactsimpartner_contactsid PK · custom fields → jsonb columns
accountsimpartner_accountsid PK · linked to impartner_contacts
dealsimpartner_dealsid PK · linked to impartner_contacts
activitiesimpartner_activitiestimestamptz events

FAQ

How does Datrise handle Impartner's custom fields in Neon?

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 Neon types.

How does the Impartner to Neon sync stay up to date?

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

Related pipelines

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