DatriseAI-first ETL

Delighted ClickHouse

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

How Datrise loads Delighted into ClickHouse

Datrise syncs Delighted's surveys, responses, scores, and follow-up workflows 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

Delighted: NPS and micro-survey feedback platform.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Delighted entities map to ClickHouse

Delighted entityClickHouse objectNotes
surveysdelighted_surveysid PK · custom fields → JSON or Map columns
responsesdelighted_responsesid PK · linked to delighted_surveys
scoresdelighted_scoresid PK · linked to delighted_surveys
follow-up workflowsdelighted_follow_up_workflowsid PK · linked to delighted_surveys

FAQ

How does Datrise handle Delighted'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 Delighted 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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