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Database ⇄ Marketing

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

Keep Google Cloud SQL and Iterable 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 Google Cloud SQL and Iterable

Give your team Iterable's contacts, campaigns, and engagement in Google Cloud SQL: query them with SQL, push audiences built from your own data back to Iterable, and skip the marketing API.

Iterable holds the people, audiences, and campaign activity that marketing runs on, but that data sits behind interfaces built for marketers, not for your internal systems. Engineers and analysts who need contacts, list membership, or engagement, for reporting, attribution, or product logic, end up writing integration code against a rate-limited API and maintaining it forever. Meanwhile the customer and usage data marketers want for targeting already lives in Google Cloud SQL, hard to get into campaigns without manual exports.

Stacksync mirrors Export data, Users, Events, Campaigns from Iterable into Databases, Schemas, Tables, Rows in Google Cloud SQL field by field, in real time, and in both directions. Marketing records become rows your code can query and join with product and customer data; audiences and attributes computed in Google Cloud SQL, from usage, orders, or account status, sync back into Iterable to drive campaigns and ads, with Iterable kept authoritative for engagement. You decide which side owns which fields, and Stacksync resolves conflicts by rules you set.

Common use cases

  • 01 Keep an internal admin application backed by Cloud SQL consistent with an ERP or billing system.
  • 02 Migrate from a self-managed database by syncing Cloud SQL and the legacy system during cutover.
  • 03 Two-way sync User profiles and their custom data fields between Iterable and a Postgres database or CRM so attributes and subscription state stay aligned in both systems.
  • 04 Push warehouse or CRM audience segments into Iterable as Users via bulkUpdate (up to 1000 per call) and subscribe them to static Lists to drive campaigns.

Common sync patterns

Engagement and results next to the customer

Opens, clicks, sends, RSVPs, or ad activity from Iterable land in Google Cloud SQL beside the matching customer record, ready for reporting and revenue attribution.

React to marketing changes as row changes

A new lead, form fill, or list change in Iterable arrives as a row change in Google Cloud SQL, so scoring, jobs, and notifications run in the tooling your team already uses.

Keep contact attributes consistent

Lifecycle stage, subscription status, or plan maintained on either side stays current on the other, ending exports and dual data entry.

What you can sync between Google Cloud SQL and Iterable

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.

Google Cloud SQL objects Iterable objects How this pairing syncs
Tables Mapped directly to sync targets; schema changes can be propagated. Catalogs Named catalogs of items (products, content) used for personalization and recommendations; items upserted and read via /api/catalogs/{catalogName}/items. Tables is specific to Google Cloud SQL and Catalogs to Iterable — each maps to any object or custom field on the other side.
Rows Read and written by primary key during each sync cycle. Commerce / Purchases Purchase and cart activity tracked via /api/commerce/trackPurchase and /api/commerce/updateCart, feeding revenue attribution and abandoned-cart journeys. Rows is specific to Google Cloud SQL and Commerce / Purchases to Iterable — each maps to any object or custom field on the other side.
Views Read-only sources for shaping data before syncing it out. Export data Historical user and event records pulled through the Export API (/api/export/data.json, data.csv, and userEvents) across data types like emailSend, emailOpen, emailClick, emailBounce, purchase, and customEvent. Views is specific to Google Cloud SQL and Export data to Iterable — each maps to any object or custom field on the other side.
Transaction logs MySQL binlog or PostgreSQL WAL, the source for log-based change capture. Users User profiles keyed by email or userId with custom data fields; upserted via POST /api/users/update, read via GET /api/users/{email} or getByUserId, bulk-written via /api/users/bulkUpdate (up to 1000 users per call), and deleted or GDPR-forgotten. Transaction logs is specific to Google Cloud SQL and Users to Iterable — each maps to any object or custom field on the other side.
Instances The managed MySQL, PostgreSQL, or SQL Server server a sync connects to. Events Custom and system events tracked via /api/events/track and /api/events/trackBulk (up to 1000 events per call); a single user's event history is read via GET /api/events/{email}. Instances is specific to Google Cloud SQL and Events to Iterable — each maps to any object or custom field on the other side.
Databases Scope the tables included in a sync configuration. Campaigns Email, SMS, push, and in-app sends; metadata and metrics read via GET /api/campaigns and /api/campaigns/metrics, created and sent via /api/campaigns/create and /api/campaigns/trigger. Databases is specific to Google Cloud SQL and Campaigns to Iterable — each maps to any object or custom field on the other side.

How changes propagate between Google Cloud SQL and Iterable

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.

Google Cloud SQL Iterable 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 Iterable through its API, with automatic retries and rate-limit backoff.

Iterable Google Cloud SQL Sub-second propagation

DetectionIterable notifies Stacksync of record changes through webhook events. System Webhooks push email/SMS/push/in-app and custom events (send, open, click, bounce, complaint, unsubscribe) as JSON POSTs in near real time.

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

Rate-limit considerations

  • Google Cloud SQL: Constrained by instance size and connection limits rather than API quotas.
  • Iterable: Limits are per endpoint and per project/key; exceeding one returns HTTP 429, so exponential backoff is advised. Event tracking allows far higher volume than metadata endpoints like campaigns/templates, and the Export API is throttled more tightly. Since Nov 10, 2025, passing the key in the query string or body is rate-limited more strictly than the Api-Key header.
What ships with Google Cloud SQL ⇄ Iterable

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

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

Observability

Monitoring

Track your Google Cloud SQL ⇄ Iterable sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Google Cloud SQL and Iterable.

How the Google Cloud SQL and Iterable connectors work

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.

Iterable

Integration surface
Iterable REST API (JSON over HTTPS): Users, Events, Campaigns, Templates, Lists, Catalogs, and Commerce endpoints, plus a bulk Export API for historical data
Authentication
API key sent in the Api-Key HTTP header (also accepted as Api_Key; the name is case-insensitive). Keys are scoped by type - Server-side, JavaScript (Web SDK), or Mobile - with optional JWT-enabled keys. US projects use api.iterable.com; EU projects use api.eu.iterable.com.
Change detection
System Webhooks push email/SMS/push/in-app and custom events (send, open, click, bounce, complaint, unsubscribe) as JSON POSTs in near real time; historical backfill and incremental catch-up run through the Export API over a date range.
Capabilities
read · write · webhooks
Rate limits
Limits are per endpoint and per project/key; exceeding one returns HTTP 429, so exponential backoff is advised. Event tracking allows far higher volume than metadata endpoints like campaigns/templates, and the Export API is throttled more tightly. Since Nov 10, 2025, passing the key in the query string or body is rate-limited more strictly than the Api-Key header.
How it works

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

    Choose tables

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

Google Cloud SQL and Iterable 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
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 395 integrations available for Google Cloud SQL and Iterable.

Popular · 8 of 395
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