Google Cloud SQL to Microsoft SQL Server Integration
AI-first ETL from Google Cloud SQL into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.
How Datrise loads Google Cloud SQL into Microsoft SQL Server
Datrise syncs Google Cloud SQL's tables, rows, schemas, indexes, read replicas, and binlog changes into Microsoft SQL Server as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.
Sync is incremental: Datrise uses a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.
Ideal for Microsoft-stack analytics and Power BI Import models.
Endpoints
Google Cloud SQL: Managed MySQL, PostgreSQL, and SQL Server instances on GCP.
Microsoft SQL Server: Microsoft relational DB with enterprise features.
How Google Cloud SQL entities map to Microsoft SQL Server
| Google Cloud SQL entity | Microsoft SQL Server object | Notes |
|---|---|---|
| tables | google_cloud_sql_tables | id PK · custom fields → NVARCHAR(MAX) JSON 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 Microsoft SQL Server?
Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft SQL Server types.
How does the Google Cloud SQL to Microsoft SQL Server sync stay up to date?
It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.
Related pipelines
More destinations for Google Cloud SQL
- Google Cloud SQL → Oracle Database
- Google Cloud SQL → Snowflake
- Google Cloud SQL → Google BigQuery
- Google Cloud SQL → Amazon Redshift
- 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
More sources for Microsoft SQL Server
- Google Cloud Storage → Microsoft SQL Server
- Google Directory → Microsoft SQL Server
- Google Ecommerce → Microsoft SQL Server
- Google PageSpeed Insights → Microsoft SQL Server
- Greenhouse → Microsoft SQL Server
- Gridly → Microsoft SQL Server
- Harness → Microsoft SQL Server
- Harvest Forecast → Microsoft SQL Server
- Heap → Microsoft SQL Server
- Hellobaton → Microsoft SQL Server
- Heroku → Microsoft SQL Server
- PostgreSQL → Microsoft SQL Server
Early access
Connect Google Cloud SQL to Microsoft SQL Server 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.