DatriseAI-first ETL

Desk.com to ClickHouse Integration

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

How Datrise loads Desk.com into ClickHouse

Datrise syncs Desk.com's cases, customers, interactions, agents, labels, and replies 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

Desk.com: Customer support ticketing and case history.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Desk.com entities map to ClickHouse

Desk.com entityClickHouse objectNotes
casesdesk_com_casesid PK · custom fields → JSON or Map columns
customersdesk_com_customersid PK · linked to desk_com_cases
interactionsdesk_com_interactionsid PK · linked to desk_com_cases
agentsdesk_com_agentsid PK · linked to desk_com_cases

FAQ

How does Datrise handle Desk.com'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 Desk.com 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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