Skip to content
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.

  • 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

Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
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.

Syncing Airtable with BigQuery moves operational data managed in Bases into warehouse-scale analytics. Airtable Records flow into BigQuery Tables organized by Datasets and Projects, so the flexible data teams maintain in Airtable becomes part of the same analytical layer as the rest of the company's data.

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

  • 01 Analytics teams join Airtable Records with warehouse data in BigQuery Tables without CSV exports.
  • 02 Data engineers use Clustered tables to keep queries over high-volume Airtable-sourced data efficient.
  • 03 BI dashboards read from BigQuery Datasets that stay current with Airtable Views.
  • 04 Feed ML feature tables in BigQuery from operational systems on a continuous schedule

Common sync patterns

Base-to-warehouse pipeline

Airtable Tables and Records load into BigQuery Tables within governed Datasets, keeping Fields mapped to columns for SQL analysis.

Partitioned history

Airtable Record changes accumulate in BigQuery Partitioned tables for point-in-time analysis of how the base evolved.

Cross-project consolidation

multiple Airtable Bases sync into BigQuery Datasets across Projects for a unified analytical model.

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 How this pairing syncs
Tables Map to sync tables; schema is readable through the base metadata endpoints. Tables The syncable unit: only tables can be synced per the Stacksync docs. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Collaborators User fields useful for mapping record ownership to accounts in a CRM or database. Datasets Organizational container — you pick which dataset’s tables to sync. Collaborators is specific to Airtable and Datasets to BigQuery — each maps to any object or custom field on the other side.
Bases Top-level containers; each base has its own API endpoint and schema. Projects Connection scope: the service account grants access per project. Bases is specific to Airtable and Projects to BigQuery — each maps to any object or custom field on the other side.
Records The row-level unit created, updated, and deleted during syncs, identified by rec-prefixed IDs. Partitioned tables Synced like regular tables; partition columns map to target fields. Records is specific to Airtable and Partitioned tables to BigQuery — each maps to any object or custom field on the other side.
Fields Typed columns including linked records, lookups, and rollups; computed fields are read-only in syncs. Clustered tables Supported; clustering is transparent to the sync. Fields is specific to Airtable and Clustered tables to BigQuery — each maps to any object or custom field on the other side.

How changes propagate between Airtable 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.

Airtable BigQuery Sub-second propagation

DetectionAirtable pushes changes as they happen — webhook events backed by change data capture. Incremental updates: changes in Airtable are detected and synced efficiently in realtime (webhook-based — creator role required to create webhooks).

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

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

Rate-limit considerations

  • Airtable: The Web API enforces a per-base limit of 5 requests per second.
  • 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 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
Try interactive demo
FAQ

Airtable 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.

Learn more about security
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
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 577 integrations available for Airtable and BigQuery.

Popular · 8 of 577
All Airtable integrations All BigQuery integrations Browse all integrations
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.

Book a demo Tour the platform on your own