DatriseAI-first ETL

Mssql SQL Server Spotfire

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

How Datrise loads Mssql SQL Server into Spotfire

Datrise syncs Mssql SQL Server's records, events, and configuration objects into Spotfire as warehouse tables or in-memory data for Spotfire analyses. Flexible or custom fields land in flattened columns for visualizations, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables or in-memory data, so re-runs update only what changed. Date-partitioned facts. Spotfire can load data in-memory, so Datrise keeps the backing tables incremental so analyses refresh without full reloads.

Ideal for interactive analytical visualization and data science.

Endpoints

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

Spotfire: Visual analytics platform for interactive dashboards and data science workflows.

How Mssql SQL Server entities map to Spotfire

Mssql SQL Server entitySpotfire objectNotes
recordsmssql_sql_server_recordsid PK · custom fields → flattened columns for visualizations
eventsmssql_sql_server_eventsdate/time 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 Spotfire?

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

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

It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.

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