DatriseAI-first ETL

CallRail to ClickHouse Integration

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

How Datrise loads CallRail into ClickHouse

Datrise syncs CallRail's calls, trackers, form submissions, sources, call outcomes, and recordings 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

CallRail: Call tracking and marketing attribution.

ClickHouse: Columnar OLAP engine for fast aggregations.

How CallRail entities map to ClickHouse

CallRail entityClickHouse objectNotes
callscallrail_callsid PK · custom fields → JSON or Map columns
trackerscallrail_trackersid PK · linked to callrail_calls
form submissionscallrail_form_submissionsid PK · linked to callrail_calls
sourcescallrail_sourcesid PK · linked to callrail_calls

FAQ

How does Datrise handle CallRail'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 CallRail 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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