DatriseAI-first ETL

Azure Table Storage Apache Superset

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

How Datrise loads Azure Table Storage into Apache Superset

Datrise syncs Azure Table Storage's records, events, and configuration objects 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

Azure Table Storage: SaaS or API data source for analytics and warehouse sync.

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

How Azure Table Storage entities map to Apache Superset

Azure Table Storage entityApache Superset objectNotes
recordsazure_table_storage_recordsid PK · custom fields → flattened columns for the explore UI
eventsazure_table_storage_eventstemporal columns for time-series charts events
configuration objectsazure_table_storage_configuration_objectsid PK · linked to azure_table_storage_records

FAQ

How does Datrise handle Azure Table Storage'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 Azure Table Storage to Apache Superset sync stay up to date?

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

Related pipelines

Early access

Connect Azure Table Storage to Apache Superset the easy way

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