DatriseAI-first ETL

Zendesk Sell Microsoft SQL Server

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

How Datrise loads Zendesk Sell into Microsoft SQL Server

Datrise syncs Zendesk Sell's leads, deals, activities, and Zendesk-aligned sales operations 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

Zendesk Sell: Sales CRM for lead and deal tracking in Zendesk ecosystems.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Zendesk Sell entities map to Microsoft SQL Server

Zendesk Sell entityMicrosoft SQL Server objectNotes
leadszendesk_sell_leadsid PK · custom fields → NVARCHAR(MAX) JSON columns
dealszendesk_sell_dealsid PK · linked to zendesk_sell_leads
activitieszendesk_sell_activitiesdatetime2 events
Zendesk-aligned sales operationszendesk_sell_zendesk_aligned_sales_operationsid PK · linked to zendesk_sell_leads

FAQ

How does Datrise handle Zendesk Sell'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 Zendesk Sell 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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