DatriseAI-first ETL

Amazon DynamoDB to Yellowfin Integration

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

How Datrise loads Amazon DynamoDB into Yellowfin

Datrise syncs Amazon DynamoDB's tables, items, partition keys, sort keys, attributes, and stream records into Yellowfin as warehouse tables Yellowfin builds views on. 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 connected tables, so re-runs update only what changed. Date-partitioned facts. Yellowfin views reference columns by name, so Datrise lands stable, well-typed columns to keep reports valid.

Ideal for dashboards with automated data storytelling.

Endpoints

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

Yellowfin: BI suite with dashboards, automated insights, and data storytelling.

How Amazon DynamoDB entities map to Yellowfin

Amazon DynamoDB entityYellowfin 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 Yellowfin?

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 Yellowfin types.

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

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

Early access

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