DatriseAI-first ETL

MongoDB ClickHouse

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

How Datrise loads MongoDB into ClickHouse

Datrise syncs MongoDB's collections, documents, change streams, and schema snapshots into ClickHouse as a MergeTree table per source entity. Flexible or custom fields land in JSON or Map columns, and timestamps such as created, updated, and status changes are typed as DateTime64.

Sync is incremental: Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge, so re-runs update only what changed. Partition by month and order by (entity id, updated-at) for fast range scans. ClickHouse deduplicates asynchronously on merge, so Datrise uses ReplacingMergeTree and FINAL-safe queries rather than assuming immediate upserts.

Ideal for high-volume event analytics that need sub-second aggregation.

Endpoints

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

ClickHouse: Columnar OLAP engine for fast aggregations.

How MongoDB entities map to ClickHouse

MongoDB entityClickHouse objectNotes
collectionsmongodb_collectionsid PK · custom fields → JSON or Map columns
documentsmongodb_documentsid PK · linked to mongodb_collections
change streamsmongodb_change_streamsDateTime64 events
schema snapshotsmongodb_schema_snapshotsid PK · linked to mongodb_collections

FAQ

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

Flexible values are stored as JSON or Map columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native ClickHouse types.

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

It runs incrementally — Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge.

Related pipelines

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