DatriseAI-first ETL

Microsoft SQL Server to Amazon QuickSight Integration

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

How Datrise loads Microsoft SQL Server into Amazon QuickSight

Datrise syncs Microsoft SQL Server's tables, rows, schemas, indexes, primary keys, and change tracking into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

Microsoft SQL Server: Microsoft SQL Server transactional databases.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How Microsoft SQL Server entities map to Amazon QuickSight

Microsoft SQL Server entityAmazon QuickSight objectNotes
tablesmssql_sql_server_tablesid PK · custom fields → flattened columns for analyses
rowsmssql_sql_server_rowsid PK · linked to mssql_sql_server_tables
schemasmssql_sql_server_schemasid PK · linked to mssql_sql_server_tables
indexesmssql_sql_server_indexesid PK · linked to mssql_sql_server_tables

FAQ

How does Datrise handle Microsoft SQL Server's custom fields in Amazon QuickSight?

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

How does the Microsoft SQL Server to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

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