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CRM ⇄ Data warehouse

Apollo.io to BigQuery integration — real-time, two-way sync

Keep Apollo.io 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 Apollo.io and BigQuery

Sync Apollo.io 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. Custom fields, Contacts, Accounts, People (database records) from Apollo.io land in BigQuery as live tables, updated within seconds, and columns computed in BigQuery write back to fields in Apollo.io. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.

Common use cases

  • Deduplicate contacts across Apollo and the CRM by syncing on email as the match key.
  • Push CRM opportunity stages back into Apollo so reps see pipeline context while sequencing.
  • Activate modeled BigQuery tables by syncing computed attributes back into sales and marketing tools
  • Maintain a customer master table in BigQuery joined across CRM, billing, and support sources

A single customer view

Join Apollo.io's relationship data with billing, product, and support data in BigQuery to build the customer picture the CRM alone cannot hold.

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 Apollo.io are queryable in BigQuery moments after they change, so dashboards stop lagging the reality they describe.

What you can sync between Apollo.io 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.

Apollo.io objects BigQuery objects
Contacts People saved to your Apollo account, synced with emails, phone numbers, and enrichment fields. Clustered tables Supported; clustering is transparent to the sync.
Accounts Company records with firmographic attributes, matched to CRM accounts during sync. Datasets Organizational container — you pick which dataset’s tables to sync.
People (database records) Prospects from Apollo's global database, pulled into downstream systems once enriched or saved. Projects Connection scope: the service account grants access per project.
Sequences Outreach cadences (emailer campaigns in the API); enrollment status is read to track which contacts are being worked. Tables The syncable unit: only tables can be synced per the Stacksync docs.
Deals (Opportunities) Pipeline records that can be read and written to keep Apollo aligned with the CRM of record. Partitioned tables Synced like regular tables; partition columns map to target fields.
What ships with Apollo.io ⇄ BigQuery

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apollo.io 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 Apollo.io or BigQuery record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Apollo.io and BigQuery connectors work

Apollo.io

Integration surface
REST API
Authentication
API key (passed in request headers); master keys unlock account-wide endpoints
Change detection
Polling on updated-at timestamps; webhook callbacks exist only for delivering asynchronous enrichment results, not as a general change-event stream
Capabilities
read · write
Rate limits
Rate limits and enrichment credits vary by plan; bulk endpoints are throttled separately from single-record calls

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

    Choose tables

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

Apollo.io 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 Apollo.io and BigQuery.

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