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Database ⇄ Marketing

Apache Cassandra to Iterable integration — real-time, two-way sync

Keep Apache Cassandra 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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Why teams connect Apache Cassandra and Iterable

Give your team Iterable's contacts, campaigns, and engagement in Apache Cassandra: 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 Apache Cassandra, hard to get into campaigns without manual exports.

Stacksync mirrors Export data, Users, Events, Campaigns from Iterable into Tables, Partitions and Rows, Materialized Views, Secondary Indexes in Apache Cassandra 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 Apache Cassandra, 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 Replicate high-volume event or profile tables from Cassandra into a warehouse for analytics that CQL cannot express.
  • 02 Sync customer profile data between Cassandra and a CRM so operational apps and sales tools agree.
  • 03 Track product and revenue Events (custom events, trackPurchase, updateCart) into Iterable from an app or database so journeys trigger on live behavior.
  • 04 Export Iterable engagement data (emailSend, emailOpen, emailClick, emailBounce, purchase) into a warehouse for deliverability and campaign reporting.

Common sync patterns

Engagement and results next to the customer

Opens, clicks, sends, RSVPs, or ad activity from Iterable land in Apache Cassandra 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 Apache Cassandra, 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 Apache Cassandra 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.

Apache Cassandra objects Iterable objects How this pairing syncs
User-Defined Types Composite column types that syncs must flatten or map to structured fields. 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. User-Defined Types is specific to Apache Cassandra and Campaigns to Iterable — each maps to any object or custom field on the other side.
Collections List, set, and map columns handled with type-aware field mapping. 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. Collections is specific to Apache Cassandra and Templates to Iterable — each maps to any object or custom field on the other side.
Counters Increment-only counter columns, usually read-only in 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. Counters is specific to Apache Cassandra and Lists to Iterable — each maps to any object or custom field on the other side.
Keyspaces Top-level namespaces with replication settings that scope a sync connection. Catalogs Named catalogs of items (products, content) used for personalization and recommendations; items upserted and read via /api/catalogs/{catalogName}/items. Keyspaces is specific to Apache Cassandra and Catalogs to Iterable — each maps to any object or custom field on the other side.
Tables Wide-column tables addressed by partition key, the unit of row-level sync. Commerce / Purchases Purchase and cart activity tracked via /api/commerce/trackPurchase and /api/commerce/updateCart, feeding revenue attribution and abandoned-cart journeys. Tables is specific to Apache Cassandra and Commerce / Purchases to Iterable — each maps to any object or custom field on the other side.
Partitions and Rows Records located by partition and clustering keys during reads and upserts. 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. Partitions and Rows is specific to Apache Cassandra and Export data to Iterable — each maps to any object or custom field on the other side.

How changes propagate between Apache Cassandra 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.

Apache Cassandra Iterable Sub-second propagation

DetectionChanges in Apache Cassandra are captured at the source via change data capture — no polling loop against its API. Commit-log based CDC on tables with CDC enabled, or polling using writetime metadata and timestamp columns.

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

Iterable Apache Cassandra 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 written to Apache Cassandra through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Apache Cassandra: No API quotas; throughput is governed by cluster capacity and consistency-level choices.
  • 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 Apache Cassandra ⇄ Iterable

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Cassandra 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 Apache Cassandra or Iterable record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Apache Cassandra and Iterable connectors work

Apache Cassandra

Integration surface
CQL over the Cassandra native binary protocol
Authentication
Database credentials (password authenticator); TLS and role-based grants where configured
Change detection
Commit-log based CDC on tables with CDC enabled, or polling using writetime metadata and timestamp columns
Capabilities
read · write · CDC
Rate limits
No API quotas; throughput is governed by cluster capacity and consistency-level choices

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 Apache Cassandra 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 Apache Cassandra 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
    Apache Cassandra connected
    Iterable connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Apache Cassandra 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.

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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 390 integrations available for Apache Cassandra and Iterable.

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