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Data warehouse ⇄ CRM

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

Keep BigQuery and Salesforce 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 Salesforce

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

Revenue-operations and data teams replicate Salesforce into BigQuery to analyze the funnel at warehouse scale. Opportunities, Accounts, and Campaigns sync into BigQuery Tables organized by Dataset, joining CRM data with product and finance sources without hitting Salesforce API limits from every dashboard.

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

Common use cases

  • 01 Analyze Cases in BigQuery alongside account revenue to spot support-driven churn risk.
  • 02 Score Leads and Accounts in BigQuery and sync results back to Salesforce fields.
  • 03 Retain full Opportunity history in BigQuery for cohort and forecast analysis.
  • 04 Sync Accounts, Contacts, and Opportunities bi-directionally with Postgres so engineering teams read and write CRM data with plain SQL.

Common sync patterns

Funnel analytics

Leads and Opportunities sync into partitioned BigQuery Tables for conversion and pipeline reporting.

Account 360

Salesforce Accounts and Contacts land in a BigQuery Dataset joined to usage and billing data.

Campaign attribution

Campaigns replicate to clustered BigQuery Tables to tie marketing spend to Opportunity outcomes.

What you can sync between BigQuery and Salesforce

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 Salesforce objects How this pairing syncs
Projects Connection scope: the service account grants access per project. Tasks and Events Activity records; usually read-only in syncs to feed activity reporting. Projects is specific to BigQuery and Tasks and Events to Salesforce — 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. Products and Price Books Catalog and pricing data; commonly mastered in an ERP and written into Salesforce. Tables is specific to BigQuery and Products and Price Books to Salesforce — each maps to any object or custom field on the other side.
Partitioned tables Synced like regular tables; partition columns map to target fields. Custom Objects Org-specific tables with the __c suffix; discoverable via describe metadata so field mappings can be generated. Partitioned tables is specific to BigQuery and Custom Objects to Salesforce — each maps to any object or custom field on the other side.
Clustered tables Supported; clustering is transparent to the sync. Accounts Company records that anchor most syncs; typically mapped to customer tables in a database or ERP. Clustered tables is specific to BigQuery and Accounts to Salesforce — each maps to any object or custom field on the other side.
Datasets Organizational container — you pick which dataset’s tables to sync. Contacts People linked to Accounts; synced two-way with marketing, support, and warehouse person records. Datasets is specific to BigQuery and Contacts to Salesforce — each maps to any object or custom field on the other side.

How changes propagate between BigQuery and Salesforce

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

Salesforce BigQuery Sub-second propagation

DetectionChanges in Salesforce are captured at the source via change data capture — no polling loop against its API. Apex triggers are used whenever possible (Salesforce actively notifies Stacksync via an Apex trigger + callout class + remote site setting).

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.
  • Salesforce: Daily API request allocations vary by edition and license count.
What ships with BigQuery ⇄ Salesforce

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever BigQuery or Salesforce 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 Salesforce record.

Observability

Monitoring

Track your BigQuery ⇄ Salesforce 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 Salesforce.

How the BigQuery and Salesforce 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

Salesforce

Integration surface
REST, SOAP, and Bulk APIs
Authentication
OAuth login via a Salesforce user (browser-based authorization flow); requires "API Enabled" permission for polling mode, plus "Author Apex" and "Customize Application" OR "Modify All Data" for trigger mode
Change detection
Apex triggers are used whenever possible (Salesforce actively notifies Stacksync via an Apex trigger + callout class + remote site setting)
Capabilities
read · write · CDC
Rate limits
Daily API request allocations vary by edition and license count.
Salesforce setup guide
How it works

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

    Choose tables

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

BigQuery and Salesforce 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 573 integrations available for BigQuery and Salesforce.

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