MongoDB → DuckDB
AI-first ETL from MongoDB into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads MongoDB into DuckDB
Datrise syncs MongoDB's collections, documents, change streams, and schema snapshots 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
MongoDB: Document database often used as an operational source for analytics.
DuckDB: In-process analytics database for fast local OLAP.
How MongoDB entities map to DuckDB
| MongoDB entity | DuckDB object | Notes |
|---|---|---|
| collections | mongodb_collections | id PK · custom fields → JSON or STRUCT columns |
| documents | mongodb_documents | id PK · linked to mongodb_collections |
| change streams | mongodb_change_streams | TIMESTAMP WITH TIME ZONE events |
| schema snapshots | mongodb_schema_snapshots | id PK · linked to mongodb_collections |
FAQ
How does Datrise handle MongoDB'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 MongoDB 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
More destinations for MongoDB
Early access
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