Google Cloud SQL → Azure Synapse

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

How Datrise loads Google Cloud SQL into Azure Synapse

Datrise syncs Google Cloud SQL's records, events, and configuration objects into Azure Synapse 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 COPY into staging, then a MERGE on stable id, so re-runs update only what changed. Hash distribution on the join id with date partitioning on facts. Synapse dedicated pools reward good hash-distribution choices, so Datrise distributes on entity ids to avoid data-movement-heavy joins.

Ideal for Azure analytics estates feeding Power BI.

Endpoints

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

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Google Cloud SQL entities map to Azure Synapse

Google Cloud SQL entity	Azure Synapse object	Notes
records	`google_cloud_sql_records`	id PK · custom fields → NVARCHAR(MAX) JSON columns
events	`google_cloud_sql_events`	datetime2 events
configuration objects	`google_cloud_sql_configuration_objects`	id PK · linked to google_cloud_sql_records

FAQ

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

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 Azure Synapse types.

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

It runs incrementally — Datrise uses COPY into staging, then a MERGE on stable id.

Related pipelines

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