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Data warehouse ⇄ CRM

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

Keep BigQuery and Nimble 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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Migrated from Mulesoft
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Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect BigQuery and Nimble

Sync Nimble 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. Companies, Deals, Tasks, Activities from Nimble land in BigQuery as live tables, updated within seconds, and columns computed in BigQuery write back to fields in Nimble. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.

Common use cases

  • Consolidate contacts from marketing tools into Nimble while writing Nimble edits back to avoid duplicates.
  • Feed Nimble activity and task data into reporting dashboards without manual CSV exports.
  • 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

Scores and segments back on the record

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

A single customer view

Join Nimble'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.

What you can sync between BigQuery and Nimble

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 Nimble objects
Tables The syncable unit: only tables can be synced per the Stacksync docs. Tasks To-do items tied to contacts, mirrored into work-management tools or reporting tables
Partitioned tables Synced like regular tables; partition columns map to target fields. Activities Calls, events, and interaction history used for engagement reporting outside Nimble
Clustered tables Supported; clustering is transparent to the sync. Notes Free-text records attached to contacts, replicated for a complete account timeline
Datasets Organizational container — you pick which dataset’s tables to sync. Tags Segmentation labels that map to list membership or filters in downstream systems
Projects Connection scope: the service account grants access per project. Custom fields Account-defined contact attributes that carry enrichment or internal identifiers
What ships with BigQuery ⇄ Nimble

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever BigQuery or Nimble 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 Nimble record.

Observability

Monitoring

Track your BigQuery ⇄ Nimble 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 Nimble.

How the BigQuery and Nimble 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

Nimble

Integration surface
REST API (JSON)
Authentication
API key; OAuth 2.0 available for registered applications
Change detection
polling on record modification timestamps
Capabilities
read · write
Rate limits
subject to per-account API request quotas
How it works

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

    Choose tables

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

BigQuery and Nimble 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 Nimble.

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