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AI ⇄ Data warehouse

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

Keep Autopilot 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.

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Why teams connect Autopilot and BigQuery

Send the records BigQuery holds into Autopilot for embedding, classification, and scoring, and land what Autopilot produces back in BigQuery as new columns, one two-way connection instead of a batch job.

BigQuery holds the raw records the business runs on; Autopilot turns those records into embeddings, scores, labels, and summaries. The two meet wherever a warehouse row needs to be enriched by a model and the result needs somewhere durable to live. Most teams stitch that meeting together with export scripts and a queue, then spend their time keeping the glue alive.

Stacksync syncs Lists, Custom Fields, Smart Segments, Journeys (Triggers) in Autopilot with Tables, Partitioned tables, Clustered tables, Datasets in BigQuery field by field, in real time, and in both directions. Rows added or changed in BigQuery flow into Autopilot as they happen, and the Lists, Custom Fields, Smart Segments, Journeys (Triggers) that Autopilot generates land back in BigQuery as columns or tables, with field-level mapping and conflict rules in place of a custom pipeline.

The payoff is that model output stops living in a separate place from the data it describes. Once results sit in BigQuery, they join against billing, product, and usage tables already there, so you can report on quality, cost, and coverage without moving anything by hand.

Common use cases

  • 01 Add contacts to a Journey from a database event or CRM stage change to start automated onboarding or nurture sequences.
  • 02 Mirror List and Smart Segment membership into a warehouse to power attribution and audience analytics alongside other sources.
  • 03 Maintain a customer master table in BigQuery joined across CRM, billing, and support sources
  • 04 Feed ML feature tables in BigQuery from operational systems on a continuous schedule

Common sync patterns

Keep an index in step with the source

As records change in BigQuery, matching Lists, Custom Fields, Smart Segments, Journeys (Triggers) in Autopilot are inserted, updated, or removed, so what Autopilot serves reflects the warehouse instead of a stale snapshot.

One place to analyze AI results

Combine Autopilot's output with the tables already in BigQuery to report on model quality, cost, and coverage without exporting anything to a spreadsheet.

History that outlives a run

A continuously synced copy in BigQuery preserves every generated result, so outputs stay auditable even as they are overwritten or expire inside Autopilot.

What you can sync between Autopilot 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.

Autopilot objects BigQuery objects How this pairing syncs
Custom Fields User-defined contact properties (string, number, date, boolean); discovered so field keys map cleanly to destination columns. Projects Connection scope: the service account grants access per project. Custom Fields is specific to Autopilot and Projects to BigQuery — each maps to any object or custom field on the other side.
Smart Segments Rule-based dynamic audiences; membership is computed by Autopilot, so it is read-only over the API. Tables The syncable unit: only tables can be synced per the Stacksync docs. Smart Segments is specific to Autopilot and Tables to BigQuery — each maps to any object or custom field on the other side.
Journeys (Triggers) Automation journeys; a contact can be added to a journey via its trigger endpoint to start automated email or SMS sequences. Partitioned tables Synced like regular tables; partition columns map to target fields. Journeys (Triggers) is specific to Autopilot and Partitioned tables to BigQuery — each maps to any object or custom field on the other side.
Activities Per-contact activity and event history (opens, clicks, journey steps); read-only feed used for engagement reporting. Clustered tables Supported; clustering is transparent to the sync. Activities is specific to Autopilot and Clustered tables to BigQuery — each maps to any object or custom field on the other side.
Contacts Core people records (email, name, custom fields, list and segment membership); upserted two-way as the primary sync object. Datasets Organizational container — you pick which dataset’s tables to sync. Contacts is specific to Autopilot and Datasets to BigQuery — each maps to any object or custom field on the other side.

How changes propagate between Autopilot 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.

Autopilot BigQuery Interval-based propagation

DetectionStacksync polls Autopilot for changes on an incremental schedule, reading only records changed since the previous pass. No CDC.

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

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

Rate-limit considerations

  • Autopilot: The REST API is capped at 100 requests/minute per account; exceeding it returns HTTP 429. Enterprise plans can request a higher limit. Contact writes accept an array for bulk upsert, and list and segment reads paginate via a bookmark cursor.
  • 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 Autopilot ⇄ BigQuery

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Autopilot 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 Autopilot or BigQuery record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Autopilot and BigQuery connectors work

Autopilot

Integration surface
REST API (Autopilot v1); Autopilot rebranded to Ortto in 2021 and the newer Ortto API co-exists with the legacy Autopilot endpoints
Authentication
Per-account API key sent in the autopilotapikey request header (generated in account settings); requests use Content-Type application/json against https://api2.autopilothq.com/v1/
Change detection
No CDC; incremental sync polls the /contacts endpoint with bookmark cursor pagination and updated timestamps. Journey webhook actions can push specific contact events, but there is no general change-subscription webhook, so polling is the reliable path.
Capabilities
read · write
Rate limits
The REST API is capped at 100 requests/minute per account; exceeding it returns HTTP 429. Enterprise plans can request a higher limit. Contact writes accept an array for bulk upsert, and list and segment reads paginate via a bookmark cursor.
Autopilot 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 Autopilot 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 Autopilot 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
    Autopilot connected
    BigQuery connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Autopilot 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.

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→ 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 515 integrations available for Autopilot and BigQuery.

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