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Database ⇄ Data warehouse

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

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

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

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

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Why teams connect Azure SQL Database and BigQuery

Connect Azure SQL Database and BigQuery with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Operational databases and analytical warehouses want the same data at different moments. Analysts want Azure SQL Database's rows in BigQuery, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in Azure SQL Database where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in Azure SQL Database sync into BigQuery in real time, and result tables in BigQuery sync back into Azure SQL Database, with schema and type mapping between the two systems handled for you.

Common use cases

  • Land CRM and ERP records in BigQuery continuously so dashboards reflect business systems without nightly batch jobs
  • Activate modeled BigQuery tables by syncing computed attributes back into sales and marketing tools
  • Feed an Azure SQL operational database with orders and inventory from an ERP in near real time.
  • Expose SaaS data (billing, support tickets) as tables in Azure SQL for reporting teams already on Microsoft tooling.

Fresh analytics without loading windows

Because changes stream continuously, analysts query current data instead of waiting for last night's load.

Offload heavy reads

Point analytical queries at the synced copy in BigQuery and keep Azure SQL Database focused on its operational workload.

Operational data in the warehouse, minus the pipeline

Rows from Azure SQL Database land in BigQuery as they change, replacing hand-built CDC and batch extract jobs.

What you can sync between Azure SQL Database and BigQuery

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 BigQuery objects
Change tracking / CDC tables System-maintained change records used to drive incremental sync. Tables The syncable unit: only tables can be synced per the Stacksync docs.
Tables The primary sync target; rows map one-to-one to records in the paired system. Partitioned tables Synced like regular tables; partition columns map to target fields.
Views Read-only projections used when the sync should expose a curated shape rather than raw tables. Clustered tables Supported; clustering is transparent to the sync.
Schemas Namespaces that organize tables and control which objects a sync user can reach. Datasets Organizational container — you pick which dataset’s tables to sync.
Rows and columns Standard relational records with typed columns; primary keys anchor upserts. Projects Connection scope: the service account grants access per project.
What ships with Azure SQL Database ⇄ BigQuery

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

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

Real-time

Two-way sync

Changes in Azure SQL Database or BigQuery 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 BigQuery 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 BigQuery record.

Observability

Monitoring

Track your Azure SQL Database ⇄ BigQuery 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 BigQuery.

How the Azure SQL Database and BigQuery 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

BigQuery

Integration surface
GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs
Authentication
Google Cloud service account: create a dedicated service account, grant roles (BigQuery Data Editor, BigQuery Job User, Cloud Functions Service Agent, Cloud Run Developer, Eventarc Event Receiver
Change detection
Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen") with a Cloud Run "secure portal for real-time notification service in
Capabilities
read · write · CDC
Rate limits
Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes
BigQuery setup guide
How it works

How to connect Azure SQL Database to BigQuery — 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 BigQuery 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
    BigQuery connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Azure SQL Database and BigQuery 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 ⇄ BigQuery
    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 BigQuery
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Azure SQL Database and BigQuery integration FAQ

SECURITY

Security teams love 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
CSA STAR
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 386 integrations available for Azure SQL Database and BigQuery.

Popular · 8 of 386
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