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Data warehouse ⇄ CRM

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

Keep BigQuery and Close 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 BigQuery and Close

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

The CRM feeds the warehouse and the warehouse should feed the CRM: relationship data flows one way, and computed scores, segments, and customer context flow back. Most teams build the first half as a batch pipeline and never quite get to the second.

Stacksync does both with one connection. Contacts, Opportunities, Activities, Tasks from Close land in BigQuery as live tables, updated within seconds, and columns computed in BigQuery write back to fields in Close. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.

Common use cases

  • Write product usage or firmographic data from an internal database onto Close lead custom fields to prioritize follow-up.
  • Sync Close leads and opportunities into Postgres or a warehouse for pipeline reporting outside Close's built-in reports.
  • Land CRM and ERP records in BigQuery continuously so dashboards reflect business systems without nightly batch jobs
  • Activate modeled BigQuery tables by syncing computed attributes back into sales and marketing tools

Cleanup that sticks

Deduplication and normalization done in BigQuery can be written back, so warehouse-side cleanup actually fixes the CRM.

CRM analytics on live data

Accounts, contacts, and activity from Close are queryable in BigQuery moments after they change, so dashboards stop lagging the reality they describe.

Scores and segments back on the record

Lead scores, churn risk, or usage segments computed in BigQuery appear as fields in Close, where the people working accounts actually see them.

What you can sync between BigQuery and Close

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 Close objects
Partitioned tables Synced like regular tables; partition columns map to target fields. Users Sales reps referenced as owners on leads, opportunities, and activities.
Clustered tables Supported; clustering is transparent to the sync. Smart Views Saved lead searches that can scope which records a segment-based sync pulls.
Datasets Organizational container — you pick which dataset’s tables to sync. Leads The top-level record in Close; represents a company and holds its contacts, opportunities, and activity history.
Projects Connection scope: the service account grants access per project. Contacts People nested under a lead, with emails and phone numbers used for outreach syncs.
Tables The syncable unit: only tables can be synced per the Stacksync docs. Opportunities Deal records with value, confidence, and status; commonly synced to reporting and billing systems.
What ships with BigQuery ⇄ Close

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever BigQuery or Close 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 Close record.

Observability

Monitoring

Track your BigQuery ⇄ Close 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 Close.

How the BigQuery and Close 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

Close

Integration surface
REST API
Authentication
API key (sent via HTTP Basic auth)
Change detection
Webhook subscriptions for record events, with polling on date_updated fields for backfills
Capabilities
read · write · webhooks
Rate limits
Subject to per-endpoint rate limits communicated in response headers
How it works

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

    Choose tables

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

BigQuery and Close 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 BigQuery and Close.

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