DatriseAI-first ETL

Amazon Rds Yellowfin

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

How Datrise loads Amazon Rds into Yellowfin

Datrise syncs Amazon Rds's records, events, and configuration objects 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 Rds: SaaS or API data source for analytics and warehouse sync.

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

How Amazon Rds entities map to Yellowfin

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

FAQ

How does Datrise handle Amazon Rds'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 Rds 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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