DatriseAI-first ETL

Freshdesk PostgreSQL

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

How Datrise loads Freshdesk into PostgreSQL

Datrise syncs Freshdesk's tickets, contacts, agents, SLA events, and satisfaction scores 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

Freshdesk: Customer support helpdesk with tickets, SLAs, and agent workflows.

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

How Freshdesk entities map to PostgreSQL

Freshdesk entityPostgreSQL objectNotes
ticketsfreshdesk_ticketsid PK · custom fields → jsonb columns
contactsfreshdesk_contactsid PK · linked to freshdesk_tickets
agentsfreshdesk_agentsid PK · linked to freshdesk_tickets
SLA eventsfreshdesk_sla_eventstimestamptz events

FAQ

How does Datrise handle Freshdesk'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 Freshdesk 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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