DatriseAI-first ETL

Mssql SQL Server Redash

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

How Datrise loads Mssql SQL Server into Redash

Datrise syncs Mssql SQL Server's records, events, and configuration objects into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, 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 for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.

Ideal for lightweight, query-driven dashboards.

Endpoints

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

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Mssql SQL Server entities map to Redash

Mssql SQL Server entityRedash objectNotes
recordsmssql_sql_server_recordsid PK · custom fields → flattened columns for query results
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 Redash?

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

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

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

Related pipelines

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