DatriseAI-first ETL

CallRail to PostgreSQL Integration

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

How Datrise loads CallRail into PostgreSQL

Datrise syncs CallRail's calls, trackers, form submissions, sources, call outcomes, and recordings 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

CallRail: Call tracking and marketing attribution.

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

How CallRail entities map to PostgreSQL

CallRail entityPostgreSQL objectNotes
callscallrail_callsid PK · custom fields → jsonb columns
trackerscallrail_trackersid PK · linked to callrail_calls
form submissionscallrail_form_submissionsid PK · linked to callrail_calls
sourcescallrail_sourcesid PK · linked to callrail_calls

FAQ

How does Datrise handle CallRail'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 CallRail 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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