DatriseAI-first ETL

Braze to ClickHouse Integration

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

How Datrise loads Braze into ClickHouse

Datrise syncs Braze's users, campaigns, canvases, message events, segments, and custom attributes 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

Braze: Cross-channel customer engagement platform.

ClickHouse: Columnar OLAP engine for fast aggregations.

How Braze entities map to ClickHouse

Braze entityClickHouse objectNotes
usersbraze_usersid PK · custom fields → JSON or Map columns
campaignsbraze_campaignsid PK · linked to braze_users
canvasesbraze_canvasesid PK · linked to braze_users
message eventsbraze_message_eventsDateTime64 events

FAQ

How does Datrise handle Braze'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 Braze 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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