DatriseAI-first ETL

Source Dynamodb GoodData

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

How Datrise loads Source Dynamodb into GoodData

Datrise syncs Source Dynamodb's records, events, and configuration objects 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

Source Dynamodb: SaaS or API data source for analytics and warehouse sync.

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

How Source Dynamodb entities map to GoodData

Source Dynamodb entityGoodData objectNotes
recordssource_dynamodb_recordsid PK · custom fields → flattened columns
eventssource_dynamodb_eventsdate dimensions events
configuration objectssource_dynamodb_configuration_objectsid PK · linked to source_dynamodb_records

FAQ

How does Datrise handle Source 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 Source Dynamodb to GoodData sync stay up to date?

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

Related pipelines

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