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Security and identity ⇄ Data warehouse

Azure Active Directory to BigQuery integration — real-time, two-way sync

Keep Azure Active Directory 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.

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

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Why teams connect Azure Active Directory and BigQuery

Land the users, groups, and access events from Azure Active Directory in BigQuery continuously for security analytics, and write computed results back — without building or maintaining a pipeline.

Azure Active Directory is the record of who exists and what they can reach; BigQuery is where the business measures everything else. The two overlap on people and their access — the same users, groups, roles, and events that Azure Active Directory governs are what security, compliance, and analytics teams want to query in BigQuery. Getting them there usually means a brittle export that runs overnight and hands auditors a snapshot that is already out of date.

Stacksync syncs Directory roles, Devices, Users, Groups from Azure Active Directory into tables in BigQuery in real time, and the connection works in both directions: values computed in BigQuery, such as risk scores or access-review decisions, can be written back to attributes in Azure Active Directory where the identity team acts on them. Schema changes are handled, API limits are managed, and the sync is something you configure rather than a pipeline you keep alive.

Common use cases

  • 01 Maintain a customer master table in BigQuery joined across CRM, billing, and support sources
  • 02 Feed ML feature tables in BigQuery from operational systems on a continuous schedule
  • 03 Reconcile Entra ID Users and assignedLicenses with an ITSM or finance database to audit license allocation and reclaim unused seats.
  • 04 Provision and deprovision Entra ID Users and Group memberships from an HR system of record so account enablement follows employment status.

Common sync patterns

Risk and review results back on the account

Risk scores, anomaly flags, or access-review outcomes computed in BigQuery write back to attributes on the matching user in Azure Active Directory, where the identity team can act on them.

Directory data in the warehouse, minus the pipeline

Users, groups, and roles from Azure Active Directory arrive in BigQuery as queryable tables, current within seconds instead of a nightly directory export.

Access and sign-in analytics

Sign-in and access events from Azure Active Directory land in BigQuery, so security and compliance teams can query who reached what, and when, alongside the rest of the business's data.

What you can sync between Azure Active Directory 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 Active Directory objects BigQuery objects How this pairing syncs
Groups /groups covering security and Microsoft 365 groups; created, updated, and deleted through Graph, and read into warehouses for entitlement reporting. Datasets Organizational container — you pick which dataset’s tables to sync. Groups is specific to Azure Active Directory and Datasets to BigQuery — each maps to any object or custom field on the other side.
Group memberships Member and owner relationships on /groups/{id}/members; added and removed via the $ref endpoint and tracked for changes with delta query on $select=members. Projects Connection scope: the service account grants access per project. Group memberships is specific to Azure Active Directory and Projects to BigQuery — each maps to any object or custom field on the other side.
Applications App registrations under /applications; usually read into a database or CMDB for app ownership and credential-expiry tracking. Tables The syncable unit: only tables can be synced per the Stacksync docs. Applications is specific to Azure Active Directory and Tables to BigQuery — each maps to any object or custom field on the other side.
Service principals /servicePrincipals (enterprise apps) plus appRoleAssignments; read for app inventory and access-posture reporting. Partitioned tables Synced like regular tables; partition columns map to target fields. Service principals is specific to Azure Active Directory and Partitioned tables to BigQuery — each maps to any object or custom field on the other side.
Directory roles /directoryRoles and roleManagement assignments; read for privileged-access reviews, with role-assignment writes where the granted scopes permit. Clustered tables Supported; clustering is transparent to the sync. Directory roles is specific to Azure Active Directory and Clustered tables to BigQuery — each maps to any object or custom field on the other side.

How changes propagate between Azure Active Directory and BigQuery

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 Active Directory BigQuery Sub-second propagation

DetectionAzure Active Directory notifies Stacksync of record changes through webhook events. Microsoft Graph delta query (deltaLink tokens returning only changed users and groups, with @removed deletions) paired with change-notification.

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

BigQuery Azure Active Directory Sub-second propagation

DetectionChanges in BigQuery are captured at the source via change data capture — no polling loop against its API. Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen").

DeliveryEach detected change is written to Azure Active Directory through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Azure Active Directory: Resource-unit throttling: roughly 8,000 ResourceUnits per 10 seconds per app for reads on tenants over 500 users, writes near 3,000 requests per 2.5 minutes; 429 responses include a Retry-After header.
  • BigQuery: 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.
What ships with Azure Active Directory ⇄ BigQuery

Connect Azure Active Directory and BigQuery for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Azure Active Directory 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 Active Directory or BigQuery record.

Observability

Monitoring

Track your Azure Active Directory ⇄ 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 Active Directory and BigQuery.

How the Azure Active Directory and BigQuery connectors work

Azure Active Directory

Integration surface
Microsoft Graph REST API (v1.0)
Authentication
OAuth 2.0 via the Microsoft identity platform using an Entra ID app registration; app-only (client credentials) or delegated flows, with directory scopes such as User.ReadWrite.All and Group.ReadWrite.All requiring tenant admin consent
Change detection
Microsoft Graph delta query (deltaLink tokens returning only changed users and groups, with @removed deletions) paired with change-notification webhook subscriptions for near-real-time push
Capabilities
read · write · webhooks
Rate limits
Resource-unit throttling: roughly 8,000 ResourceUnits per 10 seconds per app for reads on tenants over 500 users, writes near 3,000 requests per 2.5 minutes; 429 responses include a Retry-After header

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 Active Directory 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 Active Directory 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 Active Directory connected
    BigQuery connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Azure Active Directory and BigQuery 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.

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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 540 integrations available for Azure Active Directory and BigQuery.

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