DatriseAI-first ETL

Segment ClickHouse

AI-first ETL from Segment into ClickHouse. Governed entities, incremental sync, typed landing tables.

How Datrise loads Segment into ClickHouse

Datrise syncs Segment's sources, destinations, track events, identify calls, and schema catalog 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

Segment: Customer data platform routing events to warehouses.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Segment entities map to ClickHouse

Segment entityClickHouse objectNotes
sourcessegment_sourcesid PK · custom fields → JSON or Map columns
destinationssegment_destinationsid PK · linked to segment_sources
track eventssegment_track_eventsDateTime64 events
identify callssegment_identify_callsid PK · linked to segment_sources

FAQ

How does Datrise handle Segment'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 Segment 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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