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AI ⇄ Database

Autopilot to Google Cloud SQL integration — real-time, two-way sync

Keep Autopilot and Google Cloud SQL 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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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Autopilot and Google Cloud SQL

Sync the records in Google Cloud SQL into Autopilot and land its embeddings, classifications, and generated fields back on the same rows, in real time and without a pipeline to maintain.

AI systems do not hold customers or invoices the way business apps do. What they hold is derived from your data: the vectors and metadata in a vector store, or the classifications, extracted fields, and generated text a model produces over records it was given. Google Cloud SQL is where those source records actually live. The bridge between the two is the row itself, since an item in Autopilot and the record in Google Cloud SQL it describes are two halves of the same thing, and they drift the moment one is updated without the other.

Stacksync syncs Databases, Schemas, Tables, Rows in Google Cloud SQL with Lists, Custom Fields, Smart Segments, Journeys (Triggers) in Autopilot in real time. Rows created or changed in Google Cloud SQL flow into Autopilot so inference and embedding run on current data, and the scores, labels, and generated fields Autopilot produces flow back onto the matching rows in Google Cloud SQL, mapped field by field. A change on either side appears on the other within seconds, with no extraction job or webhook plumbing to keep alive.

Because matching is by a stable identifier, every row in Google Cloud SQL stays tied to its AI-side counterpart in Autopilot. Retrieval, enrichment, and generated content always resolve back to the record they came from, so there are no orphaned vectors and no labels describing a version of a row that no longer exists.

Common use cases

  • 01 Upsert Contacts from a CRM or product database into Autopilot so new signups and profile changes flow into email and SMS journeys without manual CSV imports.
  • 02 Add contacts to a Journey from a database event or CRM stage change to start automated onboarding or nurture sequences.
  • 03 Keep an internal admin application backed by Cloud SQL consistent with an ERP or billing system.
  • 04 Migrate from a self-managed database by syncing Cloud SQL and the legacy system during cutover.

Common sync patterns

Write results back onto the record

Scores, labels, extracted fields, or generated text produced in Autopilot land on the matching row in Google Cloud SQL, next to the source data your applications already query.

Keep derived data fresh as sources change

When a row in Google Cloud SQL is updated or removed, its counterpart in Autopilot is updated or removed too, so nothing in Autopilot describes a record that has since changed or gone.

Backfill once, then stay in step

Load your existing rows from Google Cloud SQL into Autopilot to build the index or enrichment set, then let ongoing changes sync automatically instead of re-running the whole job.

What you can sync between Autopilot and Google Cloud SQL

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 Google Cloud SQL objects How this pairing syncs
Lists Static contact lists; membership is readable per list and writable by adding or removing contacts. Schemas Namespace tables in PostgreSQL and SQL Server instances. Lists is specific to Autopilot and Schemas to Google Cloud SQL — each maps to any object or custom field on the other side.
Custom Fields User-defined contact properties (string, number, date, boolean); discovered so field keys map cleanly to destination columns. Tables Mapped directly to sync targets; schema changes can be propagated. Custom Fields is specific to Autopilot and Tables to Google Cloud SQL — 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. Rows Read and written by primary key during each sync cycle. Smart Segments is specific to Autopilot and Rows to Google Cloud SQL — 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. Views Read-only sources for shaping data before syncing it out. Journeys (Triggers) is specific to Autopilot and Views to Google Cloud SQL — 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. Transaction logs MySQL binlog or PostgreSQL WAL, the source for log-based change capture. Activities is specific to Autopilot and Transaction logs to Google Cloud SQL — 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. Instances The managed MySQL, PostgreSQL, or SQL Server server a sync connects to. Contacts is specific to Autopilot and Instances to Google Cloud SQL — each maps to any object or custom field on the other side.

How changes propagate between Autopilot and Google Cloud SQL

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 Google Cloud SQL 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 Google Cloud SQL as a row-level write, with types converted between the two schemas.

Google Cloud SQL Autopilot Sub-second propagation

DetectionChanges in Google Cloud SQL are captured at the source via change data capture — no polling loop against its API. Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking.

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.
  • Google Cloud SQL: Constrained by instance size and connection limits rather than API quotas.
What ships with Autopilot ⇄ Google Cloud SQL

Connect Autopilot and Google Cloud SQL for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Autopilot or Google Cloud SQL 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 Google Cloud SQL record.

Observability

Monitoring

Track your Autopilot ⇄ Google Cloud SQL 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 Google Cloud SQL.

How the Autopilot and Google Cloud SQL 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

Google Cloud SQL

Integration surface
Native SQL wire protocols (MySQL, PostgreSQL, SQL Server) plus a REST admin API for instance management
Authentication
Database credentials; IAM database authentication is available for MySQL and PostgreSQL
Change detection
Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking; polling as a fallback
Capabilities
read · write · CDC
Rate limits
Constrained by instance size and connection limits rather than API quotas.
How it works

How to connect Autopilot to Google Cloud SQL — 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 Google Cloud SQL 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
    Google Cloud SQL connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Autopilot and Google Cloud SQL 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 ⇄ Google Cloud SQL
    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 Google Cloud SQL
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Autopilot and Google Cloud SQL 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 408 integrations available for Autopilot and Google Cloud SQL.

Popular · 7 of 408
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