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Data warehouse

Azure Synapse Analytics to BigQuery integration — real-time, two-way sync

Keep Azure Synapse Analytics 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 Synapse Analytics and BigQuery

Keep tables consistent across Azure Synapse Analytics and BigQuery, for a migration, a multi-warehouse stack, or a dataset two platforms both need.

Companies end up with two warehouses for practical reasons: a migration in progress, teams that standardized on different platforms, an acquisition, or tools that only connect to one of them. The result is the same dataset maintained twice, with duplicated pipelines and numbers that almost match.

Stacksync syncs tables between Azure Synapse Analytics and BigQuery continuously, in either or both directions. Rows changed on one platform appear on the other within seconds, with schema and type mapping handled, so both warehouses answer questions with the same data.

Common use cases

  • Consolidate SaaS data alongside lake data so analysts join both through one SQL surface.
  • Load CRM and ERP records into Synapse dedicated SQL pool tables for enterprise reporting.
  • Activate modeled BigQuery tables by syncing computed attributes back into sales and marketing tools
  • Maintain a customer master table in BigQuery joined across CRM, billing, and support sources

Shared datasets across teams

Where different teams run different warehouses, sync the curated tables both rely on so their metrics agree by construction.

Consolidation after M&A

Bring the acquired company's warehouse data across continuously instead of through one-off dumps.

Migration without a big bang

When one platform is replacing the other, keep tables mirrored while workloads move over gradually, and cut over with nothing to backfill.

What you can sync between Azure Synapse Analytics 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 Synapse Analytics objects BigQuery objects
Schemas Namespaces that separate staging, integration, and presentation layers. Projects Connection scope: the service account grants access per project.
Materialized views Precomputed aggregates that speed reads of frequently synced result sets. Tables The syncable unit: only tables can be synced per the Stacksync docs.
SQL pools Dedicated or serverless compute contexts that determine how and where queries run. Partitioned tables Synced like regular tables; partition columns map to target fields.
Tables (dedicated SQL pool) Distributed warehouse tables that serve as sync destinations for analytics workloads. Clustered tables Supported; clustering is transparent to the sync.
External tables Tables over files in the data lake, queried through serverless SQL and often read-only in syncs. Datasets Organizational container — you pick which dataset’s tables to sync.
What ships with Azure Synapse Analytics ⇄ BigQuery

Connect Azure Synapse Analytics and BigQuery for flexible, real-time data sync.

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

Real-time

Two-way sync

Changes in Azure Synapse Analytics or BigQuery instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Azure Synapse Analytics 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 Synapse Analytics or BigQuery record.

Observability

Monitoring

Track your Azure Synapse Analytics ⇄ 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 Synapse Analytics and BigQuery.

How the Azure Synapse Analytics and BigQuery connectors work

Azure Synapse Analytics

Integration surface
SQL wire protocol (TDS) with T-SQL for SQL pools; additional Spark and pipeline surfaces exist but syncs use the SQL endpoint
Authentication
SQL authentication or Microsoft Entra ID
Change detection
Polling on watermark columns; Synapse SQL pools do not expose log-based CDC for downstream consumers
Capabilities
read · write

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 Synapse Analytics 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 Synapse Analytics 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 Synapse Analytics connected
    BigQuery connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Azure Synapse Analytics 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 Synapse Analytics ⇄ 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 Synapse Analytics BigQuery
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Azure Synapse Analytics 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 Synapse Analytics and BigQuery.

Popular · 8 of 386
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