DatriseAI-first ETL

GitLab ClickHouse

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

How Datrise loads GitLab into ClickHouse

Datrise syncs GitLab's projects, merge requests, pipelines, issues, and deployment events 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

GitLab: DevOps platform for repos, CI/CD, and issue tracking.

ClickHouse: Columnar OLAP engine for fast aggregations.

How GitLab entities map to ClickHouse

GitLab entityClickHouse objectNotes
projectsgitlab_projectsid PK · custom fields → JSON or Map columns
merge requestsgitlab_merge_requestsid PK · linked to gitlab_projects
pipelinesgitlab_pipelinesid PK · linked to gitlab_projects
issuesgitlab_issuesid PK · linked to gitlab_projects

FAQ

How does Datrise handle GitLab'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 GitLab 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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