DatriseAI-first ETL

CallRail to Neon Integration

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

How Datrise loads CallRail into Neon

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

CallRail: Call tracking and marketing attribution.

Neon: Serverless Postgres destination with branching and autoscaling.

How CallRail entities map to Neon

CallRail entityNeon 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 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 CallRail 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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