DatriseAI-first ETL

MongoDB Domo

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

How Datrise loads MongoDB into Domo

Datrise syncs MongoDB's collections, documents, change streams, and schema snapshots into Domo as datasets in Domo's cloud store via connector. Flexible or custom fields land in flattened columns for Magic ETL, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses partitioned dataset updates rather than full replaces, so re-runs update only what changed. Domo dataset partitions keyed on load date. Domo stores its own copy of data, so Datrise sends incremental partitions to avoid re-uploading whole datasets.

Ideal for all-in-one cloud BI with built-in ETL.

Endpoints

MongoDB: Document database often used as an operational source for analytics.

Domo: Cloud BI platform combining data integration and executive dashboards.

How MongoDB entities map to Domo

MongoDB entityDomo objectNotes
collectionsmongodb_collectionsid PK · custom fields → flattened columns for Magic ETL
documentsmongodb_documentsid PK · linked to mongodb_collections
change streamsmongodb_change_streamsdate/time columns events
schema snapshotsmongodb_schema_snapshotsid PK · linked to mongodb_collections

FAQ

How does Datrise handle MongoDB's custom fields in Domo?

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

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

It runs incrementally — Datrise uses partitioned dataset updates rather than full replaces.

Related pipelines

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