DatriseAI-first ETL

Maximizer CRM ClickHouse

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

How Datrise loads Maximizer CRM into ClickHouse

Datrise syncs Maximizer CRM'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

Maximizer CRM: CRM for SMB teams managing pipeline, contacts, and customer activity.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Maximizer CRM entities map to ClickHouse

Maximizer CRM entityClickHouse objectNotes
contactsmaximizer_contactsid PK · custom fields → JSON or Map columns
accountsmaximizer_accountsid PK · linked to maximizer_contacts
dealsmaximizer_dealsid PK · linked to maximizer_contacts
activitiesmaximizer_activitiesDateTime64 events

FAQ

How does Datrise handle Maximizer CRM'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 Maximizer CRM 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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