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Database ⇄ Marketing

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

Keep DuckDB 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 DuckDB and Iterable

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

Stacksync mirrors Lists, Catalogs, Commerce / Purchases, Export data from Iterable into Attached databases, Database files, Schemas, Tables in DuckDB 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 DuckDB, 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 Push aggregates computed in DuckDB out to a CRM or business tools so analysis results reach operational systems.
  • 02 Use DuckDB as a transform step: read synced Parquet exports, aggregate with SQL, and write results back to an operational database.
  • 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

Engagement and results next to the customer

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

DuckDB objects Iterable objects How this pairing syncs
Attached databases Additional database files or external systems attached into one session for cross-source queries. 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. Attached databases is specific to DuckDB and Export data to Iterable — each maps to any object or custom field on the other side.
Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. 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. Database files is specific to DuckDB and Users to Iterable — each maps to any object or custom field on the other side.
Schemas Namespaces within a database used to organize tables in sync outputs. 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}. Schemas is specific to DuckDB and Events to Iterable — each maps to any object or custom field on the other side.
Tables Columnar tables created via SQL; the destination for materialized sync data. 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. Tables is specific to DuckDB and Campaigns to Iterable — each maps to any object or custom field on the other side.
Views SQL views used to shape or filter data for downstream consumers. 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. Views is specific to DuckDB and Templates to Iterable — each maps to any object or custom field on the other side.
External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. 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. External files (Parquet/CSV/JSON) is specific to DuckDB and Lists to Iterable — each maps to any object or custom field on the other side.

How changes propagate between DuckDB 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.

DuckDB Iterable Interval-based propagation

DetectionStacksync polls DuckDB for changes on an incremental schedule, reading only records changed since the previous pass. Polling or full re-reads.

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

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

Rate-limit considerations

  • DuckDB: No API rate limits; throughput is bounded by local compute and I/O.
  • 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 DuckDB ⇄ Iterable

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever DuckDB 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 DuckDB or Iterable record.

Observability

Monitoring

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

Trading partners

EDI

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

How the DuckDB and Iterable connectors work

DuckDB

Integration surface
In-process SQL engine via client libraries (Python, Node.js, JDBC, CLI); no server or network API by default
Authentication
None built in; access control is file-system level (MotherDuck adds token auth for its hosted service)
Change detection
Polling or full re-reads; no change feed or transaction log API
Capabilities
read · write
Rate limits
No API rate limits; throughput is bounded by local compute and I/O

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

    Choose tables

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

DuckDB 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
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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 DuckDB and Iterable.

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