DatriseAI-first ETL

Iterable MySQL

AI-first ETL from Iterable into MySQL. Governed entities, incremental sync, typed landing tables.

How Datrise loads Iterable into MySQL

Datrise syncs Iterable's users, campaigns, journeys, message events, and experiments into MySQL as a typed table per source entity. Flexible or custom fields land in JSON columns, and timestamps such as created, updated, and status changes are typed as DATETIME/TIMESTAMP.

Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE, so re-runs update only what changed. Optional RANGE partitioning by load date. MySQL collation matters for CRM text, so Datrise lands utf8mb4 to preserve emoji and non-Latin characters.

Ideal for operational reporting and app databases already standardized on MySQL.

Endpoints

Iterable: Cross-channel marketing automation and journeys.

MySQL: Widely used OSS relational engine (InnoDB).

How Iterable entities map to MySQL

Iterable entityMySQL objectNotes
usersiterable_usersid PK · custom fields → JSON columns
campaignsiterable_campaignsid PK · linked to iterable_users
journeysiterable_journeysid PK · linked to iterable_users
message eventsiterable_message_eventsDATETIME/TIMESTAMP events

FAQ

How does Datrise handle Iterable's custom fields in MySQL?

Flexible values are stored as JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native MySQL types.

How does the Iterable to MySQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE.

Related pipelines

Early access

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