DatriseAI-first ETL

Amazon DynamoDB to Microsoft SQL Server Integration

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

How Datrise loads Amazon DynamoDB into Microsoft SQL Server

Datrise syncs Amazon DynamoDB's tables, items, partition keys, sort keys, attributes, and stream records 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 DynamoDB: Serverless key-value and document store on AWS.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Amazon DynamoDB entities map to Microsoft SQL Server

Amazon DynamoDB entityMicrosoft SQL Server objectNotes
tablessource_dynamodb_tablesid PK · custom fields → NVARCHAR(MAX) JSON columns
itemssource_dynamodb_itemsid PK · linked to source_dynamodb_tables
partition keyssource_dynamodb_partition_keysid PK · linked to source_dynamodb_tables
sort keyssource_dynamodb_sort_keysid PK · linked to source_dynamodb_tables

FAQ

How does Datrise handle Amazon DynamoDB'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 DynamoDB 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

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