DatriseAI-first ETL

Insightly PostgreSQL

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

How Datrise loads Insightly into PostgreSQL

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

Insightly: CRM and lightweight project delivery.

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

How Insightly entities map to PostgreSQL

Insightly entityPostgreSQL 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 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 Insightly 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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