Google Cloud SQL to Amazon DynamoDB Integration
AI-first ETL from Google Cloud SQL into Amazon DynamoDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Google Cloud SQL into Amazon DynamoDB
Datrise syncs Google Cloud SQL's tables, rows, schemas, indexes, read replicas, and binlog changes into Amazon DynamoDB as an item per source record in a table per entity. Flexible or custom fields land in nested map/list attributes, and timestamps such as created, updated, and status changes are typed as ISO-8601 string or epoch number attributes.
Sync is incremental: Datrise uses PutItem/UpdateItem keyed on a partition key derived from the entity id, so re-runs update only what changed. Partition-key design on the entity id to spread throughput evenly. DynamoDB rewards access-pattern-first key design, so Datrise sets partition/sort keys from your entity ids rather than scan-heavy defaults.
Ideal for serverless apps needing single-digit-millisecond key lookups on CRM data.
Endpoints
Google Cloud SQL: Managed MySQL, PostgreSQL, and SQL Server instances on GCP.
Amazon DynamoDB: Serverless key-value and document store on AWS.
How Google Cloud SQL entities map to Amazon DynamoDB
| Google Cloud SQL entity | Amazon DynamoDB object | Notes |
|---|---|---|
| tables | google_cloud_sql_tables | id PK · custom fields → nested map/list attributes |
| 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 DynamoDB?
Flexible values are stored as nested map/list attributes, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon DynamoDB types.
How does the Google Cloud SQL to Amazon DynamoDB sync stay up to date?
It runs incrementally — Datrise uses PutItem/UpdateItem keyed on a partition key derived from the entity id.
Related pipelines
More destinations for Google Cloud SQL
- Google Cloud SQL → Looker
- Google Cloud SQL → Looker Studio
- Google Cloud SQL → Microsoft Power BI
- Google Cloud SQL → Tableau
- Google Cloud SQL → Apache Superset
- Google Cloud SQL → Metabase
- Google Cloud SQL → Amazon QuickSight
- Google Cloud SQL → Domo
- Google Cloud SQL → Sisense
- Google Cloud SQL → ThoughtSpot
- Google Cloud SQL → Qlik
- Google Cloud SQL → Mode
More sources for Amazon DynamoDB
- Google Cloud Storage → Amazon DynamoDB
- Google Directory → Amazon DynamoDB
- Google Ecommerce → Amazon DynamoDB
- Google PageSpeed Insights → Amazon DynamoDB
- Greenhouse → Amazon DynamoDB
- Gridly → Amazon DynamoDB
- Harness → Amazon DynamoDB
- Harvest Forecast → Amazon DynamoDB
- Heap → Amazon DynamoDB
- Hellobaton → Amazon DynamoDB
- Heroku → Amazon DynamoDB
- PostgreSQL → Amazon DynamoDB
Early access
Connect Google Cloud SQL to Amazon DynamoDB 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.