Dremio to Yellowfin Integration
AI-first ETL from Dremio into Yellowfin. Governed entities, incremental sync, typed landing tables.
How Datrise loads Dremio into Yellowfin
Datrise syncs Dremio's datasets, tables, reflections, query jobs, sources, and table schemas 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
Dremio: Lakehouse query engine over open table formats.
Yellowfin: BI suite with dashboards, automated insights, and data storytelling.
How Dremio entities map to Yellowfin
| Dremio entity | Yellowfin object | Notes |
|---|---|---|
| datasets | dremio_datasets | id PK · custom fields → flattened columns |
| tables | dremio_tables | id PK · linked to dremio_datasets |
| reflections | dremio_reflections | id PK · linked to dremio_datasets |
| query jobs | dremio_query_jobs | id PK · linked to dremio_datasets |
FAQ
How does Datrise handle Dremio'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 Dremio to Yellowfin sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Dremio
Early access
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