DatriseAI-first ETL

Intercom PostgreSQL

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

How Datrise loads Intercom into PostgreSQL

Datrise syncs Intercom's conversations, customer attributes, inbox events, and support engagement 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

Intercom: Customer messaging platform with CRM-style account and conversation context.

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

How Intercom entities map to PostgreSQL

Intercom entityPostgreSQL objectNotes
conversationsintercom_conversationsid PK · custom fields → jsonb columns
customer attributesintercom_customer_attributesid PK · linked to intercom_conversations
inbox eventsintercom_inbox_eventstimestamptz events
support engagementintercom_support_engagementid PK · linked to intercom_conversations

FAQ

How does Datrise handle Intercom'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 Intercom 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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