DatriseAI-first ETL

Google Cloud SQL to Spreadsheets Integration

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

How Datrise loads Google Cloud SQL into Spreadsheets

Datrise syncs Google Cloud SQL's tables, rows, schemas, indexes, read replicas, and binlog changes into Spreadsheets as a tab per source entity. Flexible or custom fields land in JSON-stringified cells for nested fields, and timestamps such as created, updated, and status changes are typed as ISO-8601 text or serial date cells.

Sync is incremental: Datrise uses refreshes the tab's rows each run, preserving header order, so re-runs update only what changed. Sheets caps out around the low millions of cells, so Datrise lands a curated column set rather than every raw field.

Ideal for lightweight, shareable reporting for non-technical teams.

Endpoints

Google Cloud SQL: Managed MySQL, PostgreSQL, and SQL Server instances on GCP.

Spreadsheets: Business-friendly spreadsheet destination for collaborative analysis.

How Google Cloud SQL entities map to Spreadsheets

Google Cloud SQL entitySpreadsheets objectNotes
tablesgoogle_cloud_sql_tablesid PK · custom fields → JSON-stringified cells for nested fields
rowsgoogle_cloud_sql_rowsid PK · linked to google_cloud_sql_tables
schemasgoogle_cloud_sql_schemasid PK · linked to google_cloud_sql_tables
indexesgoogle_cloud_sql_indexesid PK · linked to google_cloud_sql_tables

FAQ

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

Flexible values are stored as JSON-stringified cells for nested fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Spreadsheets types.

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

It runs incrementally — Datrise uses refreshes the tab's rows each run, preserving header order.

Related pipelines

Early access

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