DatriseAI-first ETL

Amazon RDS to Microsoft SQL Server Integration

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

How Datrise loads Amazon RDS into Microsoft SQL Server

Datrise syncs Amazon RDS's tables, rows, schemas, indexes, primary keys, and change streams into Microsoft SQL Server as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.

Ideal for Microsoft-stack analytics and Power BI Import models.

Endpoints

Amazon RDS: Managed relational database service on AWS.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Amazon RDS entities map to Microsoft SQL Server

Amazon RDS entityMicrosoft SQL Server objectNotes
tablesamazon_rds_tablesid PK · custom fields → NVARCHAR(MAX) JSON columns
rowsamazon_rds_rowsid PK · linked to amazon_rds_tables
schemasamazon_rds_schemasid PK · linked to amazon_rds_tables
indexesamazon_rds_indexesid PK · linked to amazon_rds_tables

FAQ

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

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft SQL Server types.

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

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

Related pipelines

Early access

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