DatriseAI-first ETL

Customer.io to ClickHouse Integration

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

How Datrise loads Customer.io into ClickHouse

Datrise syncs Customer.io's people, segments, campaigns, message events, attributes, and broadcasts 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

Customer.io: Behavioral messaging across email, push, and SMS.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Customer.io entities map to ClickHouse

Customer.io entityClickHouse objectNotes
peoplecustomerio_peopleid PK · custom fields → JSON or Map columns
segmentscustomerio_segmentsid PK · linked to customerio_people
campaignscustomerio_campaignsid PK · linked to customerio_people
message eventscustomerio_message_eventsDateTime64 events

FAQ

How does Datrise handle Customer.io'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 Customer.io 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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