DatriseAI-first ETL

Azure Blob Storage to CSV Files Integration

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

How Datrise loads Azure Blob Storage into CSV Files

Datrise syncs Azure Blob Storage's containers, blobs, blob metadata, snapshots, access tiers, and blob versions 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 Blob Storage: Object storage for blobs and data lake files on Azure.

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

How Azure Blob Storage entities map to CSV Files

Azure Blob Storage entityCSV Files objectNotes
containersazureblobstorage_containersid PK · custom fields → JSON-encoded strings for nested fields
blobsazureblobstorage_blobsid PK · linked to azureblobstorage_containers
blob metadataazureblobstorage_blob_metadataid PK · linked to azureblobstorage_containers
snapshotsazureblobstorage_snapshotsid PK · linked to azureblobstorage_containers

FAQ

How does Datrise handle Azure Blob 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 Blob 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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