DatriseAI-first ETL

Lofty ClickHouse

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

How Datrise loads Lofty into ClickHouse

Datrise syncs Lofty's contacts, accounts, deals, activities, and lifecycle 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

Lofty: Real estate CRM for leads, listings, and agent follow-up.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Lofty entities map to ClickHouse

Lofty entityClickHouse objectNotes
contactslofty_contactsid PK · custom fields → JSON or Map columns
accountslofty_accountsid PK · linked to lofty_contacts
dealslofty_dealsid PK · linked to lofty_contacts
activitieslofty_activitiesDateTime64 events

FAQ

How does Datrise handle Lofty'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 Lofty 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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