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Data warehouse ⇄ Marketing

Cloudera Data Platform to Iterable integration — real-time, two-way sync

Keep Cloudera Data Platform 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 Cloudera Data Platform and Iterable

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

Cloudera Data Platform 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 Impala tables, Kudu tables, Iceberg tables, Views in Cloudera Data Platform with Lists, Catalogs, Commerce / Purchases, Export data 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 Cloudera Data Platform — and Stacksync keeps every copy consistent and resolves conflicts by rules you set.

Common use cases

  • 01 Publish CRM or ERP records into CDP so enterprise analytics runs alongside existing data lake workloads.
  • 02 Consolidate tables from on-prem and cloud CDP environments into a single cloud warehouse target.
  • 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

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 Cloudera Data Platform holds the current state for auditing.

Enrich records with warehouse context

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

Activate a modeled audience

A segment or score built in Cloudera Data Platform — high-intent accounts, churn risk, a lifetime-value tier — lands as an audience or contact field in Iterable, so campaigns target the people your data actually points to instead of a static export.

What you can sync between Cloudera Data Platform 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.

Cloudera Data Platform objects Iterable objects How this pairing syncs
Object store / HDFS files Underlying Parquet or ORC files on HDFS or cloud storage backing the tables. Templates Reusable email/SMS/push/in-app message templates with handlebars fields; read via /api/templates and per-channel get endpoints, written via /api/templates/email/upsert and the other channel upserts. Object store / HDFS files is specific to Cloudera Data Platform and Templates to Iterable — each maps to any object or custom field on the other side.
Databases Logical namespaces in the shared Hive Metastore that group tables for access control and 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 is specific to Cloudera Data Platform and Lists to Iterable — each maps to any object or custom field on the other side.
Hive tables Warehouse tables queried over JDBC/ODBC; classic managed tables are append-oriented. Catalogs Named catalogs of items (products, content) used for personalization and recommendations; items upserted and read via /api/catalogs/{catalogName}/items. Hive tables is specific to Cloudera Data Platform and Catalogs to Iterable — each maps to any object or custom field on the other side.
Impala tables The same metastore tables served through Impala for lower-latency SQL reads. Commerce / Purchases Purchase and cart activity tracked via /api/commerce/trackPurchase and /api/commerce/updateCart, feeding revenue attribution and abandoned-cart journeys. Impala tables is specific to Cloudera Data Platform and Commerce / Purchases to Iterable — each maps to any object or custom field on the other side.
Kudu tables Storage engine tables that support row-level inserts, updates, and deletes. 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. Kudu tables is specific to Cloudera Data Platform and Export data to Iterable — each maps to any object or custom field on the other side.
Iceberg tables Open table format tables in newer CDP versions, with snapshot metadata usable for incremental reads. 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. Iceberg tables is specific to Cloudera Data Platform and Users to Iterable — each maps to any object or custom field on the other side.

How changes propagate between Cloudera Data Platform 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.

Cloudera Data Platform Iterable Interval-based propagation

DetectionStacksync polls Cloudera Data Platform for changes on an incremental schedule, reading only records changed since the previous pass. Polling via SQL on timestamp or partition columns.

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

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

Rate-limit considerations

  • Cloudera Data Platform: Constrained by cluster capacity and admission control rather than API rate limits.
  • 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 Cloudera Data Platform ⇄ Iterable

Connect Cloudera Data Platform and Iterable for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Cloudera Data Platform 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 Cloudera Data Platform or Iterable record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Cloudera Data Platform and Iterable.

How the Cloudera Data Platform and Iterable connectors work

Cloudera Data Platform

Integration surface
JDBC/ODBC over Hive and Impala SQL endpoints, plus REST management APIs
Authentication
Kerberos, LDAP, or workload user credentials, often brokered through the Knox gateway
Change detection
Polling via SQL on timestamp or partition columns; no consumer-facing change feed
Capabilities
read · write
Rate limits
Constrained by cluster capacity and admission control rather than API rate limits

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 Cloudera Data Platform 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 Cloudera Data Platform 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
    Cloudera Data Platform connected
    Iterable connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Cloudera Data Platform 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 · Cloudera Data Platform ⇄ 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
    Cloudera Data Platform Iterable
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Cloudera Data Platform 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 396 integrations available for Cloudera Data Platform and Iterable.

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