DatriseAI-first ETL

Amazon Rds GoodData

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

How Datrise loads Amazon Rds into GoodData

Datrise syncs Amazon Rds'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

Amazon Rds: SaaS or API data source for analytics and warehouse sync.

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

How Amazon Rds entities map to GoodData

Amazon Rds entityGoodData objectNotes
recordsamazon_rds_recordsid PK · custom fields → flattened columns
eventsamazon_rds_eventsdate dimensions events
configuration objectsamazon_rds_configuration_objectsid PK · linked to amazon_rds_records

FAQ

How does Datrise handle Amazon Rds'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 Rds 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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