DatriseAI-first ETL

Nimble ClickHouse

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

How Datrise loads Nimble into ClickHouse

Datrise syncs Nimble's relationship records, deals, tasks, and activity intelligence 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

Nimble: Relationship-focused CRM for SMB sales teams.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Nimble entities map to ClickHouse

Nimble entityClickHouse objectNotes
relationship recordsnimble_relationship_recordsid PK · custom fields → JSON or Map columns
dealsnimble_dealsid PK · linked to nimble_relationship_records
tasksnimble_tasksid PK · linked to nimble_relationship_records
activity intelligencenimble_activity_intelligenceDateTime64 events

FAQ

How does Datrise handle Nimble'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 Nimble 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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