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

Keep Azure Service Bus 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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Why teams connect Azure Service Bus and Google Cloud SQL

Keep Google Cloud SQL and Azure Service Bus in step: the rows in your database and the Topics, Subscriptions, Messages, Rules / Filters your engineering tools track stay consistent in real time, in both directions.

Google Cloud SQL is where your application's durable data lives; Azure Service Bus is where engineering and operations teams track the issues, events, messages, or identities that run alongside it. The two overlap constantly, a row should open a ticket, an alert should land as a record, a user in one should exist in the other, but bridging them today means per-tool integration code: auth, webhooks, pagination, rate limits, and retries, built and maintained separately for every tool.

Stacksync syncs Transaction logs, Instances, Databases, Schemas in Google Cloud SQL with Topics, Subscriptions, Messages, Rules / Filters in Azure Service Bus field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync keeps every copy consistent and resolves conflicts by rules you set, so the database and the tooling around it never drift apart.

Common use cases

  • 01 Keep an internal admin application backed by Cloud SQL consistent with an ERP or billing system.
  • 02 Migrate from a self-managed database by syncing Cloud SQL and the legacy system during cutover.
  • 03 Fan out CRM or ERP record changes to a topic and let billing, analytics, and notification subscriptions each filter with SQL rules and react without coupling to the source.
  • 04 Bridge order or workflow events off a subscription into an ERP or ticketing system as they arrive, mapping message properties and the payload to target fields.

Common sync patterns

Land tool activity as queryable rows

Records and events from Azure Service Bus arrive in Google Cloud SQL as rows, so tickets, alerts, messages, or identity changes become joinable data your services and reports read directly.

One integration pattern instead of per-tool API code

Read and write the synced tables in Google Cloud SQL and Stacksync keeps Azure Service Bus current, replacing the auth, webhooks, rate limits, and retry logic you would otherwise maintain for each tool.

React to changes on either side in near real time

Updates in Azure Service Bus arrive as row changes in Google Cloud SQL, and writes to Google Cloud SQL propagate to Azure Service Bus within seconds, so triggers, jobs, and alerts fire without polling.

What you can sync between Azure Service Bus 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 Service Bus objects Google Cloud SQL objects How this pairing syncs
Dead-letter queue A sub-queue on every queue and subscription that automatically holds messages exceeding the max delivery count or their TTL, read for inspection and reprocessing. Databases Scope the tables included in a sync configuration. Dead-letter queue is specific to Azure Service Bus and Databases to Google Cloud SQL — each maps to any object or custom field on the other side.
Scheduled / deferred messages Messages enqueued for future delivery at a set time, or deferred and set aside by sequence number for retrieval later, out of the normal receive order. Schemas Namespace tables in PostgreSQL and SQL Server instances. Scheduled / deferred messages is specific to Azure Service Bus and Schemas to Google Cloud SQL — each maps to any object or custom field on the other side.
Queues Point-to-point entity: a sender writes messages and one competing consumer at a time receives them under PeekLock, then completes or abandons each message. Tables Mapped directly to sync targets; schema changes can be propagated. Queues is specific to Azure Service Bus and Tables to Google Cloud SQL — each maps to any object or custom field on the other side.
Topics Publish/subscribe entity a publisher sends to; each message is fanned out to every subscription whose filter rules match, so many consumers get their own copy. Rows Read and written by primary key during each sync cycle. Topics is specific to Azure Service Bus and Rows to Google Cloud SQL — each maps to any object or custom field on the other side.
Subscriptions A virtual queue attached to a topic; a consumer receives its own stream of matching messages here, independent of other subscriptions on the same topic. Views Read-only sources for shaping data before syncing it out. Subscriptions is specific to Azure Service Bus and Views to Google Cloud SQL — each maps to any object or custom field on the other side.
Messages The synced unit: a body plus system and user properties, MessageId, SessionId, and TTL; capped at 256 KB on Standard and up to 100 MB on Premium over AMQP. Transaction logs MySQL binlog or PostgreSQL WAL, the source for log-based change capture. Messages is specific to Azure Service Bus and Transaction logs to Google Cloud SQL — each maps to any object or custom field on the other side.

How changes propagate between Azure Service Bus 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 Service Bus Google Cloud SQL Interval-based propagation

DetectionStacksync polls Azure Service Bus for changes on an incremental schedule, reading only records changed since the previous pass. Consumes messages as they arrive: an AMQP receiver holds an open connection and takes messages with PeekLock (lock, then complete/abandon) or.

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 Service Bus 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 written to Azure Service Bus through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Azure Service Bus: Standard tier throttles around 1,000 operations/second and returns a ServerBusy error; Premium provisions dedicated messaging units (1, 2, 4, 8, or 16) for isolated, predictable throughput. Up to 5,000 concurrent AMQP connections per namespace and 5,000 concurrent receive requests per entity.
  • Google Cloud SQL: Constrained by instance size and connection limits rather than API quotas.
What ships with Azure Service Bus ⇄ Google Cloud SQL

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

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

Real-time

Two-way sync

Changes in Azure Service Bus 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 Service Bus 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 Service Bus or Google Cloud SQL record.

Observability

Monitoring

Track your Azure Service Bus ⇄ 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 Service Bus and Google Cloud SQL.

How the Azure Service Bus and Google Cloud SQL connectors work

Azure Service Bus

Integration surface
AMQP 1.0 messaging protocol plus an HTTP/REST API; entities live under a namespace at <namespace>.servicebus.windows.net (legacy SBMP also supported)
Authentication
Microsoft Entra ID (Azure AD) RBAC with managed identities - roles Azure Service Bus Data Owner, Data Sender, and Data Receiver - or Shared Access Signature (SAS) policies scoped with Manage, Send, and Listen claims
Change detection
Consumes messages as they arrive: an AMQP receiver holds an open connection and takes messages with PeekLock (lock, then complete/abandon) or ReceiveAndDelete. No modified-date polling and no native HTTP push; Azure Event Grid can separately raise an 'active messages available' event for intermittent receivers
Capabilities
read · write
Rate limits
Standard tier throttles around 1,000 operations/second and returns a ServerBusy error; Premium provisions dedicated messaging units (1, 2, 4, 8, or 16) for isolated, predictable throughput. Up to 5,000 concurrent AMQP connections per namespace and 5,000 concurrent receive requests per entity

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 Service Bus 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 Service Bus 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 Service Bus connected
    Google Cloud SQL connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Azure Service Bus 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 Service Bus ⇄ 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 Service Bus Google Cloud SQL
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Azure Service Bus 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 314 integrations available for Azure Service Bus and Google Cloud SQL.

Popular · 8 of 314
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