PostHog to Yellowfin Integration
AI-first ETL from PostHog into Yellowfin. Governed entities, incremental sync, typed landing tables.
How Datrise loads PostHog into Yellowfin
Datrise syncs PostHog's events, persons, sessions, feature flags, cohorts, and insights into Yellowfin as warehouse tables Yellowfin builds views on. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. Yellowfin views reference columns by name, so Datrise lands stable, well-typed columns to keep reports valid.
Ideal for dashboards with automated data storytelling.
Endpoints
PostHog: Product analytics with session replay and flags.
Yellowfin: BI suite with dashboards, automated insights, and data storytelling.
How PostHog entities map to Yellowfin
| PostHog entity | Yellowfin object | Notes |
|---|---|---|
| events | posthog_events | date/time dimensions events |
| persons | posthog_persons | id PK · linked to posthog_events |
| sessions | posthog_sessions | id PK · linked to posthog_events |
| feature flags | posthog_feature_flags | id PK · linked to posthog_events |
FAQ
How does Datrise handle PostHog's custom fields in Yellowfin?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Yellowfin types.
How does the PostHog to Yellowfin sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for PostHog
Early access
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