DatriseAI-first ETL

Azure Blob Storage to DuckDB Integration

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

How Datrise loads Azure Blob Storage into DuckDB

Datrise syncs Azure Blob Storage's containers, blobs, blob metadata, snapshots, access tiers, and blob versions into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

Azure Blob Storage: Object storage for blobs and data lake files on Azure.

DuckDB: In-process analytics database for fast local OLAP.

How Azure Blob Storage entities map to DuckDB

Azure Blob Storage entityDuckDB objectNotes
containersazureblobstorage_containersid PK · custom fields → JSON or STRUCT columns
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 DuckDB?

Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.

How does the Azure Blob Storage to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

Early access

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