MongoDB → Redash
AI-first ETL from MongoDB into Redash. Governed entities, incremental sync, typed landing tables.
How Datrise loads MongoDB into Redash
Datrise syncs MongoDB's collections, documents, change streams, and schema snapshots into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.
Ideal for lightweight, query-driven dashboards.
Endpoints
MongoDB: Document database often used as an operational source for analytics.
Redash: Open-source SQL client for queries, visualizations, and dashboards.
How MongoDB entities map to Redash
| MongoDB entity | Redash object | Notes |
|---|---|---|
| collections | mongodb_collections | id PK · custom fields → flattened columns for query results |
| documents | mongodb_documents | id PK · linked to mongodb_collections |
| change streams | mongodb_change_streams | temporal columns events |
| schema snapshots | mongodb_schema_snapshots | id PK · linked to mongodb_collections |
FAQ
How does Datrise handle MongoDB's custom fields in Redash?
Flexible values are stored as flattened columns for query results, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Redash types.
How does the MongoDB to Redash 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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