DatriseAI-first ETL

Zendesk ClickHouse

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

How Datrise loads Zendesk into ClickHouse

Datrise syncs Zendesk's tickets, users, organizations, macros, and satisfaction ratings 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

Zendesk: Customer support suite with tickets and knowledge base.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Zendesk entities map to ClickHouse

Zendesk entityClickHouse objectNotes
ticketszendesk_ticketsid PK · custom fields → JSON or Map columns
userszendesk_usersid PK · linked to zendesk_tickets
organizationszendesk_organizationsid PK · linked to zendesk_tickets
macroszendesk_macrosid PK · linked to zendesk_tickets

FAQ

How does Datrise handle Zendesk'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 Zendesk 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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