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Database

Azure SQL Database to Google Cloud SQL integration — real-time, two-way sync

Keep Azure SQL Database and Google Cloud SQL in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Azure SQL Database and Google Cloud SQL

Keep Azure SQL Database and Google Cloud SQL synchronized in real time, across engines, regions, or services, in one or both directions.

Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.

Stacksync syncs tables or collections between Azure SQL Database and Google Cloud SQL continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.

Common use cases

  • 01 Consolidate data from several line-of-business apps into one Azure SQL database as an integration hub.
  • 02 Feed an Azure SQL operational database with orders and inventory from an ERP in near real time.
  • 03 Migrate from a self-managed database by syncing Cloud SQL and the legacy system during cutover.
  • 04 Keep an internal admin application backed by Cloud SQL consistent with an ERP or billing system.

Common sync patterns

Regional or environment copies

Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.

Cross-engine sync

Keep the same dataset live in both Azure SQL Database and Google Cloud SQL, so each workload runs on the engine that suits it.

Migration with zero-downtime cutover

When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.

What you can sync between Azure SQL Database and Google Cloud SQL

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Azure SQL Database objects Google Cloud SQL objects How this pairing syncs
Tables The primary sync target; rows map one-to-one to records in the paired system. Tables Mapped directly to sync targets; schema changes can be propagated. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Views Read-only projections used when the sync should expose a curated shape rather than raw tables. Views Read-only sources for shaping data before syncing it out. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Schemas Namespaces that organize tables and control which objects a sync user can reach. Schemas Namespace tables in PostgreSQL and SQL Server instances. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Stored procedures Existing business logic that some teams invoke on write instead of direct table inserts. Instances The managed MySQL, PostgreSQL, or SQL Server server a sync connects to. Stored procedures is specific to Azure SQL Database and Instances to Google Cloud SQL — each maps to any object or custom field on the other side.
Change tracking / CDC tables System-maintained change records used to drive incremental sync. Databases Scope the tables included in a sync configuration. Change tracking / CDC tables is specific to Azure SQL Database and Databases to Google Cloud SQL — each maps to any object or custom field on the other side.
Rows and columns Standard relational records with typed columns; primary keys anchor upserts. Rows Read and written by primary key during each sync cycle. Rows and columns is specific to Azure SQL Database and Rows to Google Cloud SQL — each maps to any object or custom field on the other side.

How changes propagate between Azure SQL Database and Google Cloud SQL

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Azure SQL Database Google Cloud SQL Sub-second propagation

DetectionChanges in Azure SQL Database are captured at the source via change data capture — no polling loop against its API. Change data capture or change tracking, both supported on Azure SQL Database.

DeliveryEach detected change is applied to Google Cloud SQL as a row-level write, with types converted between the two schemas.

Google Cloud SQL Azure SQL Database Sub-second propagation

DetectionChanges in Google Cloud SQL are captured at the source via change data capture — no polling loop against its API. Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking.

DeliveryEach detected change is applied to Azure SQL Database as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Google Cloud SQL: Constrained by instance size and connection limits rather than API quotas.
What ships with Azure SQL Database ⇄ Google Cloud SQL

Connect Azure SQL Database and Google Cloud SQL for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Azure SQL Database–Google Cloud SQL connection.

Real-time

Two-way sync

Changes in Azure SQL Database or Google Cloud SQL instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Azure SQL Database or Google Cloud SQL data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Azure SQL Database or Google Cloud SQL record.

Observability

Monitoring

Track your Azure SQL Database ⇄ Google Cloud SQL sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Azure SQL Database and Google Cloud SQL.

How the Azure SQL Database and Google Cloud SQL connectors work

Azure SQL Database

Integration surface
SQL wire protocol (TDS), the same protocol as SQL Server; T-SQL over standard drivers
Authentication
SQL authentication (database credentials) or Microsoft Entra ID authentication
Change detection
Change data capture or change tracking, both supported on Azure SQL Database; polling as a fallback
Capabilities
read · write · CDC

Google Cloud SQL

Integration surface
Native SQL wire protocols (MySQL, PostgreSQL, SQL Server) plus a REST admin API for instance management
Authentication
Database credentials; IAM database authentication is available for MySQL and PostgreSQL
Change detection
Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking; polling as a fallback
Capabilities
read · write · CDC
Rate limits
Constrained by instance size and connection limits rather than API quotas.
How it works

How to connect Azure SQL Database to Google Cloud SQL — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Azure SQL Database and Google Cloud SQL with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Azure SQL Database connected
    Google Cloud SQL connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Azure SQL Database and Google Cloud SQL objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Azure SQL Database ⇄ Google Cloud SQL
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Azure SQL Database Google Cloud SQL
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Azure SQL Database and Google Cloud SQL integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

Learn more about security
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 374 integrations available for Azure SQL Database and Google Cloud SQL.

Popular · 2 of 374
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