DatriseAI-first ETL

FullStory MySQL

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

How Datrise loads FullStory into MySQL

Datrise syncs FullStory's sessions, events, funnels, frustration signals, and user properties 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

FullStory: Digital experience analytics with session replay context.

MySQL: Widely used OSS relational engine (InnoDB).

How FullStory entities map to MySQL

FullStory entityMySQL objectNotes
sessionsfullstory_sessionsid PK · custom fields → JSON columns
eventsfullstory_eventsDATETIME/TIMESTAMP events
funnelsfullstory_funnelsid PK · linked to fullstory_sessions
frustration signalsfullstory_frustration_signalsid PK · linked to fullstory_sessions

FAQ

How does Datrise handle FullStory'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 FullStory 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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