DatriseAI-first ETL

Amazon DynamoDB to Holistics Integration

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

How Datrise loads Amazon DynamoDB into Holistics

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

Sync is incremental: Datrise uses incremental refresh of the modeled tables, so re-runs update only what changed. Date-partitioned facts for fast aggregates. Holistics models data as code on top of SQL, so Datrise lands stable column names to keep your models from drifting.

Ideal for as-code BI modeling on a warehouse.

Endpoints

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

Holistics: Self-service BI with modeling layers and scheduled report delivery.

How Amazon DynamoDB entities map to Holistics

Amazon DynamoDB entityHolistics objectNotes
tablessource_dynamodb_tablesid PK · custom fields → flattened columns for the modeling layer
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 Holistics?

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

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

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

Related pipelines

Early access

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