DatriseAI-first ETL

Snowflake to GoodData Integration

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

How Datrise loads Snowflake into GoodData

Datrise syncs Snowflake's databases, schemas, tables, views, query history, and warehouses 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

Snowflake: Cloud data platform with separated storage and compute.

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

How Snowflake entities map to GoodData

Snowflake entityGoodData objectNotes
databasessnowflake_databasesid PK · custom fields → flattened columns
schemassnowflake_schemasid PK · linked to snowflake_databases
tablessnowflake_tablesid PK · linked to snowflake_databases
viewssnowflake_viewsid PK · linked to snowflake_databases

FAQ

How does Datrise handle Snowflake'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 Snowflake to GoodData sync stay up to date?

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

Related pipelines

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