DatriseAI-first ETL

Azure Table Storage to Chartio Integration

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

How Datrise loads Azure Table Storage into Chartio

Datrise syncs Azure Table Storage's tables, entities, partition keys, row keys, properties, and timestamps into Chartio as SQL tables a visual-SQL explorer connects to. Flexible or custom fields land in flattened columns for visual SQL, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. Visual-SQL tools build joins from your schema, so Datrise lands clearly related tables with stable id columns.

Ideal for drag-and-drop charting over a database.

Endpoints

Azure Table Storage: Key-value NoSQL store on Azure.

Chartio: Cloud BI for exploring warehouse data with drag-and-drop charts.

How Azure Table Storage entities map to Chartio

Azure Table Storage entityChartio objectNotes
tablesazure_table_storage_tablesid PK · custom fields → flattened columns for visual SQL
entitiesazure_table_storage_entitiesid PK · linked to azure_table_storage_tables
partition keysazure_table_storage_partition_keysid PK · linked to azure_table_storage_tables
row keysazure_table_storage_row_keysid PK · linked to azure_table_storage_tables

FAQ

How does Datrise handle Azure Table Storage's custom fields in Chartio?

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

How does the Azure Table Storage to Chartio sync stay up to date?

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

Related pipelines

Early access

Connect Azure Table Storage to Chartio the easy way

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