DatriseAI-first ETL

Practifi to ClickHouse Integration

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

How Datrise loads Practifi into ClickHouse

Datrise syncs Practifi's clients, households, entities, service requests, opportunities, and review meetings 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

Practifi: Salesforce-based platform for advisory firm operations.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Practifi entities map to ClickHouse

Practifi entityClickHouse objectNotes
clientspractifi_clientsid PK · custom fields → JSON or Map columns
householdspractifi_householdsid PK · linked to practifi_clients
entitiespractifi_entitiesid PK · linked to practifi_clients
service requestspractifi_service_requestsid PK · linked to practifi_clients

FAQ

How does Datrise handle Practifi'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 Practifi 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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