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Data warehouse ⇄ Communications

BigQuery to Zoom integration — real-time, two-way sync

Keep BigQuery and Zoom 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 BigQuery and Zoom

Land the messages, calls, and events from Zoom in BigQuery as live tables, and write results back, without building or maintaining a pipeline.

Zoom produces a constant stream of activity — messages sent and received, calls placed and answered, meetings held, and the delivery and engagement events attached to them. That record is what the rest of the company wants to analyze, and it usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay to get it out.

Stacksync syncs Groups, Meetings, Webinars, Registrants from Zoom into tables in BigQuery in real time, handling schema, rate limits, and retries. Because the connection works in both directions, results computed in BigQuery — segments, contact updates, suppression flags — can be written back into fields in Zoom wherever it exposes them, so analysis lands where outreach actually happens.

Common use cases

  • 01 Push Zoom Phone call logs into an operational database so sales and support calls are logged against the right customer records.
  • 02 Keep Team Chat channel membership aligned with team and department data mastered in an operational database.
  • 03 Feed ML feature tables in BigQuery from operational systems on a continuous schedule
  • 04 Land CRM and ERP records in BigQuery continuously so dashboards reflect business systems without nightly batch jobs

Common sync patterns

Activity joined with everything else

Combine Zoom's activity with the CRM, product, and support data already in BigQuery to attribute outcomes to the touches that drove them, which no single tool can do alone.

Where Zoom accepts updates: operational write-back

Segments, contact fields, or suppression flags computed in BigQuery sync back onto records in Zoom, putting warehouse analysis where the outreach happens.

Queryable history that outlives retention

A continuously synced copy in BigQuery preserves messages, call logs, and events for reporting and audit even as they age out of Zoom or get purged inside it.

What you can sync between BigQuery and Zoom

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.

BigQuery objects Zoom objects How this pairing syncs
Datasets Organizational container — you pick which dataset’s tables to sync. Participant Reports Past-meeting and webinar attendance from the Reports and Dashboard APIs; read-only, used to write attendance onto CRM records. Datasets is specific to BigQuery and Participant Reports to Zoom — each maps to any object or custom field on the other side.
Projects Connection scope: the service account grants access per project. Zoom Phone Call Logs Call detail records and recordings from Zoom Phone (requires the Phone license); read into a database to log calls against customers. Projects is specific to BigQuery and Zoom Phone Call Logs to Zoom — each maps to any object or custom field on the other side.
Tables The syncable unit: only tables can be synced per the Stacksync docs. Team Chat Channels and Messages Chat channels, membership, and messages; listed and sent two-way to align collaboration spaces with team data. Tables is specific to BigQuery and Team Chat Channels and Messages to Zoom — each maps to any object or custom field on the other side.
Partitioned tables Synced like regular tables; partition columns map to target fields. Users Account members with license type, role, and status; created, updated, and deactivated two-way to sync with HRIS or identity systems. Partitioned tables is specific to BigQuery and Users to Zoom — each maps to any object or custom field on the other side.
Clustered tables Supported; clustering is transparent to the sync. Groups User groups that carry policy and settings; membership synced from department or team data in an operational database. Clustered tables is specific to BigQuery and Groups to Zoom — each maps to any object or custom field on the other side.

How changes propagate between BigQuery and Zoom

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.

BigQuery Zoom 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 Zoom through its API, with automatic retries and rate-limit backoff.

Zoom BigQuery Sub-second propagation

DetectionZoom notifies Stacksync of record changes through webhook events. Webhooks via Event Subscriptions (meeting.started/ended, participant joined/left, user.created/updated, recording.completed, and more) for real-time.

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

Rate-limit considerations

  • 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.
  • Zoom: APIs are grouped into Light, Medium, Heavy, and Resource-intensive categories with per-second and daily quotas that scale by plan (e.g. Business+ Heavy APIs allow 40/second within a 60,000/day combined cap); exceeding a limit returns HTTP 429.
What ships with BigQuery ⇄ Zoom

Connect BigQuery and Zoom for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever BigQuery or Zoom 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 BigQuery or Zoom record.

Observability

Monitoring

Track your BigQuery ⇄ Zoom sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between BigQuery and Zoom.

How the BigQuery and Zoom connectors work

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

Zoom

Integration surface
REST API (v2) with webhook Event Subscriptions
Authentication
OAuth 2.0 — user-authorized OAuth or Server-to-Server OAuth using account credentials; access tokens are valid for one hour and requests use granular per-resource scopes (e.g. meeting:read, user:write)
Change detection
Webhooks via Event Subscriptions (meeting.started/ended, participant joined/left, user.created/updated, recording.completed, and more) for real-time events, with polling on list endpoints using date-range filters for backfill and objects without an event
Capabilities
read · write · webhooks
Rate limits
APIs are grouped into Light, Medium, Heavy, and Resource-intensive categories with per-second and daily quotas that scale by plan (e.g. Business+ Heavy APIs allow 40/second within a 60,000/day combined cap); exceeding a limit returns HTTP 429.
How it works

How to connect BigQuery to Zoom — 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 BigQuery and Zoom 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
    BigQuery connected
    Zoom connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the BigQuery and Zoom 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 · BigQuery ⇄ Zoom
    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
    BigQuery Zoom
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

BigQuery and Zoom 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 446 integrations available for BigQuery and Zoom.

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