DatriseAI-first ETL

Mixpanel Databricks SQL Warehouse

AI-first ETL from Mixpanel into Databricks SQL Warehouse. Governed entities, incremental sync, typed landing tables.

How Datrise loads Mixpanel into Databricks SQL Warehouse

Datrise syncs Mixpanel's events, user profiles, cohorts, funnels, and retention metrics into Databricks SQL Warehouse as a Delta Lake table per source entity. Flexible or custom fields land in VARIANT or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses a Delta MERGE on stable id, with change history available via time travel, so re-runs update only what changed. Delta partitioning by load date with OPTIMIZE/Z-ORDER on query keys. Datrise writes Unity Catalog–governed Delta tables, so lineage and permissions are managed centrally rather than per-notebook.

Ideal for lakehouse analytics and ML feature tables on Databricks.

Endpoints

Mixpanel: Product analytics for events, funnels, and retention.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Mixpanel entities map to Databricks SQL Warehouse

Mixpanel entityDatabricks SQL Warehouse objectNotes
eventsmixpanel_eventsTIMESTAMP events
user profilesmixpanel_user_profilesid PK · linked to mixpanel_events
cohortsmixpanel_cohortsid PK · linked to mixpanel_events
funnelsmixpanel_funnelsid PK · linked to mixpanel_events

FAQ

How does Datrise handle Mixpanel's custom fields in Databricks SQL Warehouse?

Flexible values are stored as VARIANT or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Databricks SQL Warehouse types.

How does the Mixpanel to Databricks SQL Warehouse sync stay up to date?

It runs incrementally — Datrise uses a Delta MERGE on stable id, with change history available via time travel.

Related pipelines

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