DatriseAI-first ETL

Frontapp Microsoft SQL Server

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

How Datrise loads Frontapp into Microsoft SQL Server

Datrise syncs Frontapp's records, events, and configuration objects 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

Frontapp: SaaS or API data source for analytics and warehouse sync.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Frontapp entities map to Microsoft SQL Server

Frontapp entityMicrosoft SQL Server objectNotes
recordsfrontapp_recordsid PK · custom fields → NVARCHAR(MAX) JSON columns
eventsfrontapp_eventsdatetime2 events
configuration objectsfrontapp_configuration_objectsid PK · linked to frontapp_records

FAQ

How does Datrise handle Frontapp'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 Frontapp 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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