DatriseAI-first ETL

CircleCI to MongoDB Integration

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

How Datrise loads CircleCI into MongoDB

Datrise syncs CircleCI's pipelines, workflows, jobs, builds, test results, and artifacts into MongoDB as a collection per source entity. Flexible or custom fields land in native nested documents, and timestamps such as created, updated, and status changes are typed as BSON Date.

Sync is incremental: Datrise uses upserts by stable id with updateOne(upsert) on the source primary key, so re-runs update only what changed. Optional sharding on the entity id for large collections. Mongo has no fixed schema, so Datrise keeps field types consistent across documents to avoid mixed-type query surprises.

Ideal for document-oriented apps that want CRM data in their existing Mongo store.

Endpoints

CircleCI: Continuous integration and delivery pipelines.

MongoDB: Document database for flexible schemas.

How CircleCI entities map to MongoDB

CircleCI entityMongoDB objectNotes
pipelinescircle_ci_pipelinesid PK · custom fields → native nested documents
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 MongoDB?

Flexible values are stored as native nested documents, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native MongoDB types.

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

It runs incrementally — Datrise uses upserts by stable id with updateOne(upsert) on the source primary key.

Related pipelines

Early access

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