Snowflake to Amazon QuickSight Integration
AI-first ETL from Snowflake into Amazon QuickSight. Governed entities, incremental sync, typed landing tables.
How Datrise loads Snowflake into Amazon QuickSight
Datrise syncs Snowflake's databases, schemas, tables, views, query history, and warehouses into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.
Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.
Ideal for AWS-native dashboards with pay-per-session pricing.
Endpoints
Snowflake: Cloud data platform with separated storage and compute.
Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.
How Snowflake entities map to Amazon QuickSight
| Snowflake entity | Amazon QuickSight object | Notes |
|---|---|---|
| databases | snowflake_databases | id PK · custom fields → flattened columns for analyses |
| schemas | snowflake_schemas | id PK · linked to snowflake_databases |
| tables | snowflake_tables | id PK · linked to snowflake_databases |
| views | snowflake_views | id PK · linked to snowflake_databases |
FAQ
How does Datrise handle Snowflake's custom fields in Amazon QuickSight?
Flexible values are stored as flattened columns for analyses, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon QuickSight types.
How does the Snowflake to Amazon QuickSight sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.
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Early access
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