DatriseAI-first ETL

CallRail to Microsoft SQL Server Integration

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

How Datrise loads CallRail into Microsoft SQL Server

Datrise syncs CallRail's calls, trackers, form submissions, sources, call outcomes, and recordings into Microsoft SQL Server as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.

Ideal for Microsoft-stack analytics and Power BI Import models.

Endpoints

CallRail: Call tracking and marketing attribution.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How CallRail entities map to Microsoft SQL Server

CallRail entityMicrosoft SQL Server objectNotes
callscallrail_callsid PK · custom fields → NVARCHAR(MAX) JSON 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 Microsoft SQL Server?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft SQL Server types.

How does the CallRail to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

Related pipelines

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