PostHog to ClickHouse Integration
AI-first ETL from PostHog into ClickHouse. Governed entities, incremental sync, typed landing tables.
How Datrise loads PostHog into ClickHouse
Datrise syncs PostHog's events, persons, sessions, feature flags, cohorts, and insights into ClickHouse as a MergeTree table per source entity. Flexible or custom fields land in JSON or Map columns, and timestamps such as created, updated, and status changes are typed as DateTime64.
Sync is incremental: Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge, so re-runs update only what changed. Partition by month and order by (entity id, updated-at) for fast range scans. ClickHouse deduplicates asynchronously on merge, so Datrise uses ReplacingMergeTree and FINAL-safe queries rather than assuming immediate upserts.
Ideal for high-volume event analytics that need sub-second aggregation.
Endpoints
PostHog: Product analytics with session replay and flags.
ClickHouse: Columnar OLAP engine for fast aggregations.
How PostHog entities map to ClickHouse
| PostHog entity | ClickHouse object | Notes |
|---|---|---|
| events | posthog_events | DateTime64 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 ClickHouse?
Flexible values are stored as JSON or Map columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native ClickHouse types.
How does the PostHog to ClickHouse sync stay up to date?
It runs incrementally — Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge.
Related pipelines
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