DatriseAI-first ETL

CircleCI to ClickHouse Integration

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

How Datrise loads CircleCI into ClickHouse

Datrise syncs CircleCI's pipelines, workflows, jobs, builds, test results, and artifacts 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

CircleCI: Continuous integration and delivery pipelines.

ClickHouse: Columnar OLAP engine for fast aggregations.

How CircleCI entities map to ClickHouse

CircleCI entityClickHouse objectNotes
pipelinescircle_ci_pipelinesid PK · custom fields → JSON or Map columns
workflowscircle_ci_workflowsid PK · linked to circle_ci_pipelines
jobscircle_ci_jobsid PK · linked to circle_ci_pipelines
buildscircle_ci_buildsid PK · linked to circle_ci_pipelines

FAQ

How does Datrise handle CircleCI'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 CircleCI 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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