DatriseAI-first ETL

Insightly Neon

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

How Datrise loads Insightly into Neon

Datrise syncs Insightly's contacts, organizations, opportunities, projects, and delivery milestones 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

Insightly: CRM and lightweight project delivery.

Neon: Serverless Postgres destination with branching and autoscaling.

How Insightly entities map to Neon

Insightly entityNeon objectNotes
contactsinsightly_contactsid PK · custom fields → jsonb columns
organizationsinsightly_organizationsid PK · linked to insightly_contacts
opportunitiesinsightly_opportunitiesid PK · linked to insightly_contacts
projectsinsightly_projectsid PK · linked to insightly_contacts

FAQ

How does Datrise handle Insightly'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 Insightly 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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