DatriseAI-first ETL

Azure Blob Storage to Neon Integration

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

How Datrise loads Azure Blob Storage into Neon

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

Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative partitioning by load date. Neon separates compute from storage, so Datrise batches writes to keep autoscaling compute from cold-starting on every small change.

Ideal for serverless Postgres workloads that scale to zero between syncs.

Endpoints

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

Neon: Serverless Postgres destination with branching and autoscaling.

How Azure Blob Storage entities map to Neon

Azure Blob Storage entityNeon objectNotes
containersazureblobstorage_containersid PK · custom fields → jsonb 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 Neon?

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

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

It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

Early access

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