DatriseAI-first ETL

GitLab Chartio

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

How Datrise loads GitLab into Chartio

Datrise syncs GitLab's projects, merge requests, pipelines, issues, and deployment events into Chartio as SQL tables a visual-SQL explorer connects to. Flexible or custom fields land in flattened columns for visual SQL, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. Visual-SQL tools build joins from your schema, so Datrise lands clearly related tables with stable id columns.

Ideal for drag-and-drop charting over a database.

Endpoints

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

Chartio: Cloud BI for exploring warehouse data with drag-and-drop charts.

How GitLab entities map to Chartio

GitLab entityChartio objectNotes
projectsgitlab_projectsid PK · custom fields → flattened columns for visual SQL
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 Chartio?

Flexible values are stored as flattened columns for visual SQL, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Chartio types.

How does the GitLab to Chartio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

Early access

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