Dremio to GoodData Integration
AI-first ETL from Dremio into GoodData. Governed entities, incremental sync, typed landing tables.
How Datrise loads Dremio into GoodData
Datrise syncs Dremio's datasets, tables, reflections, query jobs, sources, and table schemas 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
Dremio: Lakehouse query engine over open table formats.
GoodData: Composable analytics platform with headless BI and embedded dashboards.
How Dremio entities map to GoodData
| Dremio entity | GoodData 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 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 Dremio to GoodData 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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