DatriseAI-first ETL

CircleCI to CSV Files Integration

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

How Datrise loads CircleCI into CSV Files

Datrise syncs CircleCI's pipelines, workflows, jobs, builds, test results, and artifacts into CSV Files as one CSV per source entity. Flexible or custom fields land in JSON-encoded strings for nested fields, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.

Sync is incremental: Datrise uses writes a fresh, fully-typed CSV per entity each run, so re-runs update only what changed. Optional date-suffixed files for change tracking. CSV has no types, so Datrise emits a companion schema and quotes/escapes consistently so downstream loaders don't misparse commas and newlines.

Ideal for portable hand-off into any tool that ingests delimited files.

Endpoints

CircleCI: Continuous integration and delivery pipelines.

CSV Files: Flat-file destination for exports and lightweight data sharing.

How CircleCI entities map to CSV Files

CircleCI entityCSV Files objectNotes
pipelinescircle_ci_pipelinesid PK · custom fields → JSON-encoded strings for nested fields
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 CSV Files?

Flexible values are stored as JSON-encoded strings for nested fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native CSV Files types.

How does the CircleCI to CSV Files sync stay up to date?

It runs incrementally — Datrise uses writes a fresh, fully-typed CSV per entity each run.

Related pipelines

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