DatriseAI-first ETL

Amazon DynamoDB to Birst Integration

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

How Datrise loads Amazon DynamoDB into Birst

Datrise syncs Amazon DynamoDB's tables, items, partition keys, sort keys, attributes, and stream records into Birst as warehouse tables for Birst's automated star schema. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the source tables Birst ingests, so re-runs update only what changed. Date-partitioned facts. Birst builds its own semantic layer, so Datrise lands conformed, well-keyed tables it can automate against.

Ideal for networked, governed enterprise BI.

Endpoints

Amazon DynamoDB: Serverless key-value and document store on AWS.

Birst: Cloud BI with networked analytics and enterprise semantic layers.

How Amazon DynamoDB entities map to Birst

Amazon DynamoDB entityBirst objectNotes
tablessource_dynamodb_tablesid PK · custom fields → flattened 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 Birst?

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

How does the Amazon DynamoDB to Birst sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the source tables Birst ingests.

Related pipelines

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