DatriseAI-first ETL

Customer.io ClickHouse

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 profiles, segments, campaigns, deliveries, and conversion events 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: Messaging automation based on product and behavioral data.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Customer.io entities map to ClickHouse

Customer.io entityClickHouse objectNotes
profilescustomer_io_profilesid PK · custom fields → JSON or Map columns
segmentscustomer_io_segmentsid PK · linked to customer_io_profiles
campaignscustomer_io_campaignsid PK · linked to customer_io_profiles
deliveriescustomer_io_deliveriesid PK · linked to customer_io_profiles

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

Early access

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