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Marketing ⇄ Data warehouse

Iterable to StarRocks integration — real-time, two-way sync

Keep Iterable and StarRocks 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 Iterable and StarRocks

Put modeled data to work and measure what it drives: StarRocks and Iterable keep contacts, audiences, and campaign results in step in real time, in both directions.

StarRocks is where your team models customers, product usage, and revenue into trusted tables; Iterable runs the campaigns, audiences, and messages that reach those people. The two overlap wherever the same person, account, or segment matters to both, and when the bridge between them is a nightly export or a hand-built list, marketing targets stale data while analytics never sees what the campaign returned.

Stacksync syncs Partitions, Columns, Databases, Tables in StarRocks with Campaigns, Templates, Lists, Catalogs in Iterable field by field, in real time, and in both directions. You decide which system owns which fields — a computed score or segment can flow out to Iterable while sends, opens, and conversions flow back to StarRocks — and Stacksync keeps every copy consistent and resolves conflicts by rules you set.

Common use cases

  • 01 Consolidate several sources into StarRocks as the query layer while Stacksync handles movement
  • 02 Land CRM and ERP records into StarRocks to serve low-latency operational dashboards
  • 03 Write list subscribe/unsubscribe changes from a CRM back into Iterable Lists so suppression and opt-in state stay current before the next send.
  • 04 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.

Common sync patterns

Keep the contact and audience list current

New and updated contacts, leads, or audience members flow between StarRocks and Iterable, so the marketing audience reflects the people in your warehouse and corrections propagate instead of the two sides drifting apart.

Suppression and consent stay aligned

Unsubscribes, bounces, and consent or opt-out flags held in either system propagate to the other, so no one is messaged after opting out and StarRocks holds the current state for auditing.

Enrich records with warehouse context

Product-usage counts, plan tier, region, or account owner computed in StarRocks appear on the matching record in Iterable, so targeting, routing, and personalization use up-to-date context.

What you can sync between Iterable and StarRocks

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.

Iterable objects StarRocks objects How this pairing syncs
Lists Static subscriber lists; read via GET /api/lists and /api/lists/getUsers, with users added or removed via /api/lists/subscribe and /api/lists/unsubscribe to control who receives a send. Databases Top-level namespaces addressed exactly as in MySQL clients. Lists is specific to Iterable and Databases to StarRocks — each maps to any object or custom field on the other side.
Catalogs Named catalogs of items (products, content) used for personalization and recommendations; items upserted and read via /api/catalogs/{catalogName}/items. Tables Defined with a table model (Primary Key, Unique Key, Aggregate, Duplicate Key) that determines update behavior. Catalogs is specific to Iterable and Tables to StarRocks — each maps to any object or custom field on the other side.
Commerce / Purchases Purchase and cart activity tracked via /api/commerce/trackPurchase and /api/commerce/updateCart, feeding revenue attribution and abandoned-cart journeys. Materialized views Automatically maintained rollups used to accelerate queries on synced data. Commerce / Purchases is specific to Iterable and Materialized views to StarRocks — each maps to any object or custom field on the other side.
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 Logical views for shaping analytical reads. Export data is specific to Iterable and Views to StarRocks — each maps to any object or custom field on the other side.
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. Partitions Time or range partitions that scope loads and retention. Users is specific to Iterable and Partitions to StarRocks — each maps to any object or custom field on the other side.
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}. Columns Columnar storage with types mapped from source systems during sync. Events is specific to Iterable and Columns to StarRocks — each maps to any object or custom field on the other side.

How changes propagate between Iterable and StarRocks

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.

Iterable StarRocks 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 StarRocks as a row-level write, with types converted between the two schemas.

StarRocks Iterable Interval-based propagation

DetectionStacksync polls StarRocks for changes on an incremental schedule, reading only records changed since the previous pass. Query-based polling when reading.

DeliveryEach detected change is written to Iterable through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • 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.
  • StarRocks: Ingestion throughput is bounded by cluster resources rather than API quotas.
What ships with Iterable ⇄ StarRocks

Connect Iterable and StarRocks for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Iterable or StarRocks 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 Iterable or StarRocks record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Iterable and StarRocks.

How the Iterable and StarRocks connectors work

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.

StarRocks

Integration surface
MySQL wire protocol for SQL; HTTP-based Stream Load API for ingestion
Authentication
Database credentials (MySQL-compatible username/password)
Change detection
Query-based polling when reading; StarRocks is most often the destination side of a sync
Capabilities
read · write
Rate limits
Ingestion throughput is bounded by cluster resources rather than API quotas
How it works

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

    Choose tables

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

Iterable and StarRocks 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
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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

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