DatriseAI-first ETL

Zapier to ClickHouse Integration

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

How Datrise loads Zapier into ClickHouse

Datrise syncs Zapier's zaps, task runs, triggers, actions, connected apps, and run statuses 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

Zapier: Automation runs connecting apps through triggers.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Zapier entities map to ClickHouse

Zapier entityClickHouse objectNotes
zapszapier_zapsid PK · custom fields → JSON or Map columns
task runszapier_task_runsid PK · linked to zapier_zaps
triggerszapier_triggersid PK · linked to zapier_zaps
actionszapier_actionsid PK · linked to zapier_zaps

FAQ

How does Datrise handle Zapier'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 Zapier 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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