Azure Blob Storage to Snowflake Integration

How Datrise loads Azure Blob Storage into Snowflake

Datrise syncs Azure Blob Storage's containers, blobs, blob metadata, snapshots, access tiers, and blob versions into Snowflake as a typed table per source entity. Flexible or custom fields land in VARIANT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP_TZ.

Sync is incremental: Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size, so re-runs update only what changed. Automatic micro-partitioning, with optional clustering keys on high-cardinality ids. Snowflake upper-cases unquoted identifiers, so Datrise standardizes on lower-case quoted names to keep column references stable.

Ideal for central analytics warehouses feeding BI and AI workloads.

Endpoints

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

Snowflake: Cloud data warehouse with separated compute and storage.

How Azure Blob Storage entities map to Snowflake

Azure Blob Storage entity	Snowflake object	Notes
containers	`azureblobstorage_containers`	id PK · custom fields → VARIANT columns
blobs	`azureblobstorage_blobs`	id PK · linked to azureblobstorage_containers
blob metadata	`azureblobstorage_blob_metadata`	id PK · linked to azureblobstorage_containers
snapshots	`azureblobstorage_snapshots`	id PK · linked to azureblobstorage_containers

FAQ

How does Datrise handle Azure Blob Storage's custom fields in Snowflake?

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

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

It runs incrementally — Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size.

Related pipelines

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