DatriseAI-first ETL

EspoCRM ClickHouse

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

How Datrise loads EspoCRM into ClickHouse

Datrise syncs EspoCRM's pipeline entities, custom objects, and process automation events 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

EspoCRM: Open-source CRM for pipeline management and custom entity modeling.

ClickHouse: Columnar OLAP engine for fast aggregations.

How EspoCRM entities map to ClickHouse

EspoCRM entityClickHouse objectNotes
pipeline entitiesespocrm_pipeline_entitiesid PK · custom fields → JSON or Map columns
custom objectsespocrm_custom_objectsid PK · linked to espocrm_pipeline_entities
process automation eventsespocrm_process_automation_eventsDateTime64 events

FAQ

How does Datrise handle EspoCRM'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 EspoCRM 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.

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