DatriseAI-first ETL

Microsoft SQL Server to Mode Integration

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

How Datrise loads Microsoft SQL Server into Mode

Datrise syncs Microsoft SQL Server's tables, rows, schemas, indexes, primary keys, and change tracking into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.

Ideal for SQL-first analysis with Python and R notebooks.

Endpoints

Microsoft SQL Server: Microsoft SQL Server transactional databases.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How Microsoft SQL Server entities map to Mode

Microsoft SQL Server entityMode objectNotes
tablesmssql_sql_server_tablesid PK · custom fields → flattened columns for SQL and notebooks
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 Mode?

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

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

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

Related pipelines

Early access

Connect Microsoft SQL Server to Mode the easy way

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