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CRM ⇄ Data warehouse

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

Keep Attio 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 Attio and BigQuery

Sync Attio into BigQuery continuously and push warehouse results back onto CRM records, one two-way connection instead of two pipelines.

Syncing Attio to BigQuery brings CRM data into the analytics warehouse where it can be modeled alongside product and finance data. Attio Deals and Companies land in BigQuery Datasets as Tables, so pipeline reporting runs on warehouse SQL rather than CRM exports.

Stacksync does both with one connection. Custom objects, People, Companies, Users from Attio land in BigQuery as live tables, updated within seconds, and columns computed in BigQuery write back to fields in Attio. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.

Common use cases

  • 01 Track Deal-stage history over time using Partitioned tables.
  • 02 Cluster large People tables by company for fast account-level queries.
  • 03 Consolidate multiple Attio Workspaces into one BigQuery Project for company-wide reporting.
  • 04 Keep Attio aligned with a billing system or ERP on customer records and plan status.

Common sync patterns

Pipeline analytics

Attio Deals and Companies sync into BigQuery Tables, partitioned for efficient historical queries.

Account 360 modeling

Attio People and Custom objects join with product events in a shared Dataset.

Scored-segment writeback

segments computed in BigQuery update Attio Company records for targeting.

What you can sync between Attio 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.

Attio objects BigQuery objects How this pairing syncs
Companies Standard company object; matched to billing and product accounts in two-way syncs. Projects Connection scope: the service account grants access per project. Companies is specific to Attio and Projects to BigQuery — each maps to any object or custom field on the other side.
Users Synced with incremental and full sync per the Stacksync docs. Tables The syncable unit: only tables can be synced per the Stacksync docs. Users is specific to Attio and Tables to BigQuery — each maps to any object or custom field on the other side.
Deals Pipeline records; read out for revenue reporting and written to from automation. Partitioned tables Synced like regular tables; partition columns map to target fields. Deals is specific to Attio and Partitioned tables to BigQuery — each maps to any object or custom field on the other side.
Workspaces Synced with incremental and full sync per the Stacksync docs. Clustered tables Supported; clustering is transparent to the sync. Workspaces is specific to Attio and Clustered tables to BigQuery — each maps to any object or custom field on the other side.
Custom objects Workspace-defined objects that behave like standard ones in the API. Datasets Organizational container — you pick which dataset’s tables to sync. Custom objects is specific to Attio and Datasets to BigQuery — each maps to any object or custom field on the other side.

How changes propagate between Attio 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.

Attio BigQuery Sub-second propagation

DetectionAttio notifies Stacksync of record changes through webhook events. Webhooks on record and list-entry events, with polling as a fallback.

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

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

Rate-limit considerations

  • Attio: Subject to the platform's published API rate limits.
  • 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 Attio ⇄ BigQuery

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Attio 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 Attio or BigQuery record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Attio and BigQuery connectors work

Attio

Integration surface
REST API
Authentication
Guided in-app connection ("Attio CRM" connection created in a few clicks, "without any coding required"); the docs do not name the underlying auth mechanism (OAuth vs API key)
Change detection
Webhooks on record and list-entry events, with polling as a fallback
Capabilities
read · write · webhooks
Rate limits
Subject to the platform's published API rate limits.
Attio 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 Attio 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 Attio 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
    Attio connected
    BigQuery connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Attio 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
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 390 integrations available for Attio and BigQuery.

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