DatriseAI-first ETL

Mssql SQL Server Chartio

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

How Datrise loads Mssql SQL Server into Chartio

Datrise syncs Mssql SQL Server's records, events, and configuration objects into Chartio as SQL tables a visual-SQL explorer connects to. Flexible or custom fields land in flattened columns for visual SQL, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. Visual-SQL tools build joins from your schema, so Datrise lands clearly related tables with stable id columns.

Ideal for drag-and-drop charting over a database.

Endpoints

Mssql SQL Server: SaaS or API data source for analytics and warehouse sync.

Chartio: Cloud BI for exploring warehouse data with drag-and-drop charts.

How Mssql SQL Server entities map to Chartio

Mssql SQL Server entityChartio objectNotes
recordsmssql_sql_server_recordsid PK · custom fields → flattened columns for visual SQL
eventsmssql_sql_server_eventstemporal columns events
configuration objectsmssql_sql_server_configuration_objectsid PK · linked to mssql_sql_server_records

FAQ

How does Datrise handle Mssql SQL Server's custom fields in Chartio?

Flexible values are stored as flattened columns for visual SQL, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Chartio types.

How does the Mssql SQL Server to Chartio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

Early access

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