DatriseAI-first ETL

Azure Table Storage to CSV Files Integration

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

How Datrise loads Azure Table Storage into CSV Files

Datrise syncs Azure Table Storage's tables, entities, partition keys, row keys, properties, and timestamps into CSV Files as one CSV per source entity. Flexible or custom fields land in JSON-encoded strings for nested fields, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.

Sync is incremental: Datrise uses writes a fresh, fully-typed CSV per entity each run, so re-runs update only what changed. Optional date-suffixed files for change tracking. CSV has no types, so Datrise emits a companion schema and quotes/escapes consistently so downstream loaders don't misparse commas and newlines.

Ideal for portable hand-off into any tool that ingests delimited files.

Endpoints

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

CSV Files: Flat-file destination for exports and lightweight data sharing.

How Azure Table Storage entities map to CSV Files

Azure Table Storage entityCSV Files objectNotes
tablesazure_table_storage_tablesid PK · custom fields → JSON-encoded strings for nested fields
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 CSV Files?

Flexible values are stored as JSON-encoded strings for nested fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native CSV Files types.

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

It runs incrementally — Datrise uses writes a fresh, fully-typed CSV per entity each run.

Related pipelines

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