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Database ⇄ Data warehouse

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

Keep Airtable 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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  • 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 Airtable and BigQuery

Connect Airtable 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 Airtable'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 Airtable where the services that read from it get them at normal query latency.

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

Common use cases

  • Feed ML feature tables in BigQuery from operational systems on a continuous schedule
  • Land CRM and ERP records in BigQuery continuously so dashboards reflect business systems without nightly batch jobs
  • Push CRM accounts and deals into an Airtable base so operations teams can manage pipelines and enrichment without CRM licenses.
  • Write cleaned records edited in Airtable back to the source system of record, keeping both sides consistent in near real time.

Offload heavy reads

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

Operational data in the warehouse, minus the pipeline

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

Serve warehouse results at database speed

Aggregates or model outputs computed in BigQuery sync into Airtable, where whatever reads from that database gets them without querying the warehouse.

What you can sync between Airtable 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.

Airtable objects BigQuery objects
Linked records Cross-table references that carry relationships between synced tables. Tables The syncable unit: only tables can be synced per the Stacksync docs.
Attachments File fields exposed as expiring URLs that syncs can mirror to other systems. Partitioned tables Synced like regular tables; partition columns map to target fields.
Collaborators User fields useful for mapping record ownership to accounts in a CRM or database. Clustered tables Supported; clustering is transparent to the sync.
Bases Top-level containers; each base has its own API endpoint and schema. Datasets Organizational container — you pick which dataset’s tables to sync.
Tables Map to sync tables; schema is readable through the base metadata endpoints. Projects Connection scope: the service account grants access per project.
What ships with Airtable ⇄ BigQuery

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Airtable 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 Airtable or BigQuery record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Airtable and BigQuery connectors work

Airtable

Integration surface
REST API (per-base Web API plus metadata and webhooks endpoints)
Authentication
OAuth (Airtable OAuth grant to specific bases or all resources); the authorizing user must have a `creator` role, since only creator roles can create webhooks
Change detection
Incremental updates: changes in Airtable are detected and synced efficiently in realtime (webhook-based — creator role required to create webhooks); formula fields don't emit change events and are re-synced every hour
Capabilities
read · write · CDC · webhooks
Rate limits
The Web API enforces a per-base limit of 5 requests per second.
Airtable setup guide

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

    Choose tables

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

Airtable 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 Airtable and BigQuery.

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