DatriseAI-first ETL

Streak to ClickHouse Integration

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

How Datrise loads Streak into ClickHouse

Datrise syncs Streak's pipelines, boxes, stages, email threads, contacts, and tasks 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

Streak: CRM that lives inside Gmail as pipelines and boxes.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Streak entities map to ClickHouse

Streak entityClickHouse objectNotes
pipelinesstreak_pipelinesid PK · custom fields → JSON or Map columns
boxesstreak_boxesid PK · linked to streak_pipelines
stagesstreak_stagesid PK · linked to streak_pipelines
email threadsstreak_email_threadsid PK · linked to streak_pipelines

FAQ

How does Datrise handle Streak'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 Streak 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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