DatriseAI-first ETL

Freshsales Microsoft SQL Server

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

How Datrise loads Freshsales into Microsoft SQL Server

Datrise syncs Freshsales's leads, contacts, deals, calls, and email activity telemetry 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

Freshsales: CRM by Freshworks with built-in phone and email.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Freshsales entities map to Microsoft SQL Server

Freshsales entityMicrosoft SQL Server objectNotes
leadsfreshsales_leadsid PK · custom fields → NVARCHAR(MAX) JSON columns
contactsfreshsales_contactsid PK · linked to freshsales_leads
dealsfreshsales_dealsid PK · linked to freshsales_leads
callsfreshsales_callsid PK · linked to freshsales_leads

FAQ

How does Datrise handle Freshsales'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 Freshsales to Microsoft SQL Server sync stay up to date?

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

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