MongoDB → GoodData
AI-first ETL from MongoDB into GoodData. Governed entities, incremental sync, typed landing tables.
How Datrise loads MongoDB into GoodData
Datrise syncs MongoDB's collections, documents, change streams, and schema snapshots into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.
Ideal for embedded, multi-tenant analytics.
Endpoints
MongoDB: Document database often used as an operational source for analytics.
GoodData: Composable analytics platform with headless BI and embedded dashboards.
How MongoDB entities map to GoodData
| MongoDB entity | GoodData object | Notes |
|---|---|---|
| collections | mongodb_collections | id PK · custom fields → flattened columns |
| documents | mongodb_documents | id PK · linked to mongodb_collections |
| change streams | mongodb_change_streams | date dimensions events |
| schema snapshots | mongodb_schema_snapshots | id PK · linked to mongodb_collections |
FAQ
How does Datrise handle MongoDB's custom fields in GoodData?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native GoodData types.
How does the MongoDB to GoodData sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for MongoDB
Early access
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