DatriseAI-first ETL

Amazon RDS to Azure Synapse Integration

AI-first ETL from Amazon RDS into Azure Synapse. Governed entities, incremental sync, typed landing tables.

How Datrise loads Amazon RDS into Azure Synapse

Datrise syncs Amazon RDS's tables, rows, schemas, indexes, primary keys, and change streams into Azure Synapse 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 COPY into staging, then a MERGE on stable id, so re-runs update only what changed. Hash distribution on the join id with date partitioning on facts. Synapse dedicated pools reward good hash-distribution choices, so Datrise distributes on entity ids to avoid data-movement-heavy joins.

Ideal for Azure analytics estates feeding Power BI.

Endpoints

Amazon RDS: Managed relational database service on AWS.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Amazon RDS entities map to Azure Synapse

Amazon RDS entityAzure Synapse 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 Azure Synapse?

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 Azure Synapse types.

How does the Amazon RDS to Azure Synapse sync stay up to date?

It runs incrementally — Datrise uses COPY into staging, then a MERGE on stable id.

Related pipelines

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