Google Cloud SQL to Amazon Redshift Integration
AI-first ETL from Google Cloud SQL into Amazon Redshift. Governed entities, incremental sync, typed landing tables.
How Datrise loads Google Cloud SQL into Amazon Redshift
Datrise syncs Google Cloud SQL's tables, rows, schemas, indexes, read replicas, and binlog changes into Amazon Redshift as a typed table per source entity. Flexible or custom fields land in SUPER columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMPTZ.
Sync is incremental: Datrise uses COPY from staged files, then a delete-and-insert merge on stable id, so re-runs update only what changed. A DISTKEY on the join id and a SORTKEY on the load timestamp. Redshift performance hinges on dist/sort keys, so Datrise picks them from your entity ids and sync timestamps rather than defaulting to EVEN distribution.
Ideal for AWS-native warehouses already using the Redshift ecosystem.
Endpoints
Google Cloud SQL: Managed MySQL, PostgreSQL, and SQL Server instances on GCP.
Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.
How Google Cloud SQL entities map to Amazon Redshift
| Google Cloud SQL entity | Amazon Redshift object | Notes |
|---|---|---|
| tables | google_cloud_sql_tables | id PK · custom fields → SUPER columns |
| rows | google_cloud_sql_rows | id PK · linked to google_cloud_sql_tables |
| schemas | google_cloud_sql_schemas | id PK · linked to google_cloud_sql_tables |
| indexes | google_cloud_sql_indexes | id PK · linked to google_cloud_sql_tables |
FAQ
How does Datrise handle Google Cloud SQL's custom fields in Amazon Redshift?
Flexible values are stored as SUPER columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon Redshift types.
How does the Google Cloud SQL to Amazon Redshift sync stay up to date?
It runs incrementally — Datrise uses COPY from staged files, then a delete-and-insert merge on stable id.
Related pipelines
More destinations for Google Cloud SQL
- Google Cloud SQL → Databricks SQL Warehouse
- Google Cloud SQL → ClickHouse
- Google Cloud SQL → DuckDB
- Google Cloud SQL → Amazon Athena
- Google Cloud SQL → Amazon S3 Data Lake
- Google Cloud SQL → Azure Data Lake Storage
- Google Cloud SQL → Azure Synapse
- Google Cloud SQL → Spreadsheets
- Google Cloud SQL → Airtable
- Google Cloud SQL → CSV Files
- Google Cloud SQL → MongoDB
- Google Cloud SQL → Supabase
More sources for Amazon Redshift
- Google Cloud Storage → Amazon Redshift
- Google Directory → Amazon Redshift
- Google Ecommerce → Amazon Redshift
- Google PageSpeed Insights → Amazon Redshift
- Greenhouse → Amazon Redshift
- Gridly → Amazon Redshift
- Harness → Amazon Redshift
- Harvest Forecast → Amazon Redshift
- Heap → Amazon Redshift
- Hellobaton → Amazon Redshift
- Heroku → Amazon Redshift
- PostgreSQL → Amazon Redshift
Early access
Connect Google Cloud SQL to Amazon Redshift the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.