DatriseAI-first ETL

Azure Table Storage to Amazon Redshift Integration

AI-first ETL from Azure Table Storage into Amazon Redshift. Governed entities, incremental sync, typed landing tables.

How Datrise loads Azure Table Storage into Amazon Redshift

Datrise syncs Azure Table Storage's tables, entities, partition keys, row keys, properties, and timestamps into Amazon Redshift as a typed table per source entity. Flexible or custom fields land in SUPER columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMPTZ.

Sync is incremental: Datrise uses COPY from staged files, then a delete-and-insert merge on stable id, so re-runs update only what changed. A DISTKEY on the join id and a SORTKEY on the load timestamp. Redshift performance hinges on dist/sort keys, so Datrise picks them from your entity ids and sync timestamps rather than defaulting to EVEN distribution.

Ideal for AWS-native warehouses already using the Redshift ecosystem.

Endpoints

Azure Table Storage: Key-value NoSQL store on Azure.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Azure Table Storage entities map to Amazon Redshift

Azure Table Storage entityAmazon Redshift objectNotes
tablesazure_table_storage_tablesid PK · custom fields → SUPER columns
entitiesazure_table_storage_entitiesid PK · linked to azure_table_storage_tables
partition keysazure_table_storage_partition_keysid PK · linked to azure_table_storage_tables
row keysazure_table_storage_row_keysid PK · linked to azure_table_storage_tables

FAQ

How does Datrise handle Azure Table Storage's custom fields in Amazon Redshift?

Flexible values are stored as SUPER columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon Redshift types.

How does the Azure Table Storage to Amazon Redshift sync stay up to date?

It runs incrementally — Datrise uses COPY from staged files, then a delete-and-insert merge on stable id.

Related pipelines

Early access

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