DatriseAI-first ETL

Amazon DynamoDB to GoodData Integration

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

How Datrise loads Amazon DynamoDB into GoodData

Datrise syncs Amazon DynamoDB's tables, items, partition keys, sort keys, attributes, and stream records into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.

Ideal for embedded, multi-tenant analytics.

Endpoints

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

GoodData: Composable analytics platform with headless BI and embedded dashboards.

How Amazon DynamoDB entities map to GoodData

Amazon DynamoDB entityGoodData 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 GoodData?

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 GoodData types.

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

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

Related pipelines

Early access

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