DatriseAI-first ETL

Google Cloud SQL Redash

AI-first ETL from Google Cloud SQL into Redash. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Cloud SQL into Redash

Datrise syncs Google Cloud SQL's records, events, and configuration objects into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.

Ideal for lightweight, query-driven dashboards.

Endpoints

Google Cloud SQL: SaaS or API data source for analytics and warehouse sync.

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Google Cloud SQL entities map to Redash

Google Cloud SQL entityRedash objectNotes
recordsgoogle_cloud_sql_recordsid PK · custom fields → flattened columns for query results
eventsgoogle_cloud_sql_eventstemporal columns events
configuration objectsgoogle_cloud_sql_configuration_objectsid PK · linked to google_cloud_sql_records

FAQ

How does Datrise handle Google Cloud SQL's custom fields in Redash?

Flexible values are stored as flattened columns for query results, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Redash types.

How does the Google Cloud SQL to Redash sync stay up to date?

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

Related pipelines

Early access

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