Microsoft Azure to Azure Data Lake Storage Integration
AI-first ETL from Microsoft Azure into Azure Data Lake Storage. Governed entities, incremental sync, typed landing tables.
How Datrise loads Microsoft Azure into Azure Data Lake Storage
Datrise syncs Microsoft Azure's subscriptions, resource groups, resources, usage records, costs, and activity logs into Azure Data Lake Storage as partitioned Parquet in ADLS Gen2 per source entity. Flexible or custom fields land in nested struct/map fields in Parquet, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.
Sync is incremental: Datrise uses writes new date partitions to the container and compacts on a schedule, so re-runs update only what changed. Hive-style partitioning by load date, readable by Synapse and Databricks. ADLS hierarchical namespace makes folder layout matter, so Datrise keeps a predictable entity/date path your Azure engines mount directly.
Ideal for Azure lakehouse storage shared across Synapse and Databricks.
Endpoints
Microsoft Azure: Azure subscription resources, usage, and billing.
Azure Data Lake Storage: ADLS Gen2 object storage for analytics workloads.
How Microsoft Azure entities map to Azure Data Lake Storage
| Microsoft Azure entity | Azure Data Lake Storage object | Notes |
|---|---|---|
| subscriptions | microsoft_azure_subscriptions | id PK · custom fields → nested struct/map fields in Parquet |
| resource groups | microsoft_azure_resource_groups | id PK · linked to microsoft_azure_subscriptions |
| resources | microsoft_azure_resources | id PK · linked to microsoft_azure_subscriptions |
| usage records | microsoft_azure_usage_records | id PK · linked to microsoft_azure_subscriptions |
FAQ
How does Datrise handle Microsoft Azure's custom fields in Azure Data Lake Storage?
Flexible values are stored as nested struct/map fields in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Azure Data Lake Storage types.
How does the Microsoft Azure to Azure Data Lake Storage sync stay up to date?
It runs incrementally — Datrise uses writes new date partitions to the container and compacts on a schedule.
Related pipelines
More destinations for Microsoft Azure
- Microsoft Azure → Azure Synapse
- Microsoft Azure → Spreadsheets
- Microsoft Azure → Airtable
- Microsoft Azure → CSV Files
- Microsoft Azure → MongoDB
- Microsoft Azure → Supabase
- Microsoft Azure → Neon
- Microsoft Azure → PlanetScale
- Microsoft Azure → Amazon DynamoDB
- Microsoft Azure → Looker
- Microsoft Azure → Looker Studio
- Microsoft Azure → Microsoft Power BI
More sources for Azure Data Lake Storage
- Microsoft Dataverse → Azure Data Lake Storage
- Microsoft SharePoint → Azure Data Lake Storage
- Microsoft Teams → Azure Data Lake Storage
- Microsoft SQL Server → Azure Data Lake Storage
- My Hours → Azure Data Lake Storage
- n8n → Azure Data Lake Storage
- NetSuite SuiteAnalytics → Azure Data Lake Storage
- New York Times → Azure Data Lake Storage
- News API → Azure Data Lake Storage
- Newsdata → Azure Data Lake Storage
- Notion → Azure Data Lake Storage
- Okta → Azure Data Lake Storage
Early access
Connect Microsoft Azure to Azure Data Lake Storage the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.