DatriseAI-first ETL

FullStory PostgreSQL

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

How Datrise loads FullStory into PostgreSQL

Datrise syncs FullStory's sessions, events, funnels, frustration signals, and user properties into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

FullStory: Digital experience analytics with session replay context.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How FullStory entities map to PostgreSQL

FullStory entityPostgreSQL objectNotes
sessionsfullstory_sessionsid PK · custom fields → jsonb columns
eventsfullstory_eventstimestamptz 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 PostgreSQL?

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

How does the FullStory to PostgreSQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

Early access

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