Source connector

Iterable connector

Iterable integration for databases, warehouses and BI tools

Cross-channel marketing automation and journeys. Datrise captures Iterable entities such as users, campaigns, journeys, message events, and experiments, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

The Iterable API v1 authenticates with API key, JWT, incremental runs key on profileUpdatedAt (user profiles); startDateTime/endDateTime range on /api/export endpoints for events, and Iterable caps calls at 100 requests per second per project for most endpoints; the Export API is limited to 4 requests per minute per project.

Of the 5 objects, 4 sync as upserts keyed on the primary key and 1 as append-only streams, so each incremental run moves only what changed since the last watermark. Every object lands in its own table (for example `iterable_users`) with a schema derived from the Iterable API rather than a flattened CSV, in any of the 43 supported destinations.

Datrise is in early access: pick a destination below to open the Iterable pipeline page, and join the waitlist to get the Iterable connector (Marketing) with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Iterable data Datrise extracts

Each object lands in its own typed table. Sync mode is derived from the object: history-style objects append, everything else upserts.

Object	Landing table	Sync mode
users	iterable_users	Upsert by primary key, incremental on updated-at
campaigns	iterable_campaigns	Upsert by primary key, incremental on updated-at
journeys	iterable_journeys	Upsert by primary key, incremental on updated-at
message events	iterable_message_events	Append-only, incremental by timestamp
experiments	iterable_experiments	Upsert by primary key, incremental on updated-at

Iterable API: setup facts for the connector

Verified against the vendor documentation on 2026-09-02. Unknown values are left blank rather than guessed.

API	Iterable API v1
Authentication	API key, JWT — Every request needs an `Api-Key` header tied to a project-scoped key (Standard, Server-side, Client-side, or Mobile type); JWT-enabled API keys add a short-lived signed-token layer on top of the static key for tighter scoping.
Pagination	none — Most endpoints return a single object or a full list with no page token; bulk history is instead chunked by `startDateTime`/`endDateTime` windows on the export endpoints.
Rate limit	100 requests per second per project for most endpoints; the Export API is limited to 4 requests per minute per project
Incremental cursor	profileUpdatedAt (user profiles); startDateTime/endDateTime range on /api/export endpoints for events — Since February 2023 `profileUpdatedAt` no longer changes on a no-op update, so it is a reliable incremental cursor for the Users resource.
Webhooks	Yes — System Webhooks
Bulk export	Yes — Data Export API (/api/export/data.json, /api/export/userEvents)
Deletes detectable	No — Regular user deletes are hard deletes with no tombstone field; only GDPR-driven deletions are surfaced, via GET /api/users/forgotten returning the hashed emails of forgotten users

Official API reference

What bites when replicating Iterable

The Export API is capped at 4 requests per minute per project, ten times tighter than the general 100-requests-per-second limit, so a naive full-history export needs the date-range windows spread over many minutes to avoid HTTP 429s.
Exports are capped at roughly 100 GB total with individual files up to 10 MB, so a large `startDateTime`/`endDateTime` window must be split into smaller ranges (commonly 28 days) to stay under the per-file ceiling.
Ordinary `DELETE /api/users` calls leave no deletion record; a connector can only detect removed users by diffing full snapshots or by checking `GET /api/users/forgotten`, which lists only GDPR-forgotten users, not every delete.
As of November 10, 2025, API keys passed in the query string or request body (instead of the `Api-Key` header) are subject to stricter rate limiting, which can silently throttle scripts written against older examples.

Compare this against every other documented API

Popular destinations for Iterable

Choose a destination below to open the ready pipeline page.

A
Airtable
Relational spreadsheet destination for ops and go-to-market teams.
View pipeline
A
Amazon Athena
Serverless SQL over S3 data lake tables.
View pipeline
A
Amazon DynamoDB
Serverless key-value and document store on AWS.
View pipeline
A
Amazon QuickSight
AWS serverless BI with SPICE and embedded analytics.
View pipeline
A
Amazon Redshift
AWS petabyte-scale warehouse with Spectrum.
View pipeline
A
Amazon S3 Data Lake
Object storage landing zone for parquet and snapshots.
View pipeline
A
Apache Superset
Open-source BI for SQL exploration, charts, and dashboard publishing.
View pipeline
A
Azure Data Lake Storage
ADLS Gen2 object storage for analytics workloads.
View pipeline
A
Azure Synapse
Microsoft analytics workspace with SQL pools.
View pipeline

Iterable connector FAQ

What Iterable data does the connector extract?: 5 objects: users, campaigns, journeys, message events and experiments. Each lands in its own table with types preserved; history-style objects (1: message events) load as append-only streams.
Is the Iterable integration incremental?: Yes. After the initial full load, every run reads only records changed since the last watermark (updated-at or event timestamp) and applies an upsert or an append depending on the object.
Where can I load Iterable data?: Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Iterable → destination pair has its own page with the object-to-table mapping.

Related Marketing sources

Other sources in the same category, each with its own connector page.

Early access

Launch your Iterable pipeline with guided onboarding

Join the waitlist to get priority access for Iterable integrations with guided setup, schema-aware mapping, and production-grade incremental sync.