CircleCI to DuckDB Integration

How Datrise loads CircleCI into DuckDB

Datrise syncs CircleCI's pipelines, workflows, jobs, builds, test results, and artifacts into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

CircleCI: Continuous integration and delivery pipelines.

DuckDB: In-process analytics database for fast local OLAP.

How CircleCI entities map to DuckDB

CircleCI entity	DuckDB object	Notes
pipelines	`circle_ci_pipelines`	id PK · custom fields → JSON or STRUCT columns
workflows	`circle_ci_workflows`	id PK · linked to circle_ci_pipelines
jobs	`circle_ci_jobs`	id PK · linked to circle_ci_pipelines
builds	`circle_ci_builds`	id PK · linked to circle_ci_pipelines

FAQ

How does Datrise handle CircleCI's custom fields in DuckDB?

Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.

How does the CircleCI to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

Early access

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