DatriseAI-first ETL

Streak Apache Superset

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

How Datrise loads Streak into Apache Superset

Datrise syncs Streak's contacts, accounts, deals, activities, and lifecycle events into Apache Superset as governed SQL tables Superset queries directly. Flexible or custom fields land in flattened columns for the explore UI, and timestamps such as created, updated, and status changes are typed as temporal columns for time-series charts.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned tables to keep dashboards responsive. Superset charts run live SQL, so Datrise lands query-friendly, indexed tables rather than wide raw payloads.

Ideal for open-source dashboards over your own database.

Endpoints

Streak: CRM for SMB teams managing pipeline, contacts, and customer activity.

Apache Superset: Open-source BI for SQL exploration, charts, and dashboard publishing.

How Streak entities map to Apache Superset

Streak entityApache Superset objectNotes
contactsstreak_contactsid PK · custom fields → flattened columns for the explore UI
accountsstreak_accountsid PK · linked to streak_contacts
dealsstreak_dealsid PK · linked to streak_contacts
activitiesstreak_activitiestemporal columns for time-series charts events

FAQ

How does Datrise handle Streak's custom fields in Apache Superset?

Flexible values are stored as flattened columns for the explore UI, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Apache Superset types.

How does the Streak to Apache Superset sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

Early access

Connect Streak to Apache Superset the easy way

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