DatriseAI-first ETL

Google Sheets Microsoft SQL Server

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

How Datrise loads Google Sheets into Microsoft SQL Server

Datrise syncs Google Sheets's spreadsheet-based CRM rows, updates, and operational workflow tables 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

Google Sheets: Spreadsheet CRM workflows and lightweight pipelines.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Google Sheets entities map to Microsoft SQL Server

Google Sheets entityMicrosoft SQL Server objectNotes
spreadsheet-based CRM rowsgoogle_sheets_spreadsheet_based_crm_rowsid PK · custom fields → NVARCHAR(MAX) JSON columns
updatesgoogle_sheets_updatesid PK · linked to google_sheets_spreadsheet_based_crm_rows
operational workflow tablesgoogle_sheets_operational_workflow_tablesid PK · linked to google_sheets_spreadsheet_based_crm_rows

FAQ

How does Datrise handle Google Sheets'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 Google Sheets 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

Early access

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