Google Directory to Azure Data Lake Storage Integration
AI-first ETL from Google Directory into Azure Data Lake Storage. Governed entities, incremental sync, typed landing tables.
How Datrise loads Google Directory into Azure Data Lake Storage
Datrise syncs Google Directory's users, groups, group members, organizational units, devices, and roles 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
Google Directory: Workspace user, group, and device directory.
Azure Data Lake Storage: ADLS Gen2 object storage for analytics workloads.
How Google Directory entities map to Azure Data Lake Storage
| Google Directory entity | Azure Data Lake Storage object | Notes |
|---|---|---|
| users | google_directory_users | id PK · custom fields → nested struct/map fields in Parquet |
| groups | google_directory_groups | id PK · linked to google_directory_users |
| group members | google_directory_group_members | id PK · linked to google_directory_users |
| organizational units | google_directory_organizational_units | id PK · linked to google_directory_users |
FAQ
How does Datrise handle Google Directory'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 Google Directory 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 Google Directory
- Google Directory → Azure Synapse
- Google Directory → Spreadsheets
- Google Directory → Airtable
- Google Directory → CSV Files
- Google Directory → MongoDB
- Google Directory → Supabase
- Google Directory → Neon
- Google Directory → PlanetScale
- Google Directory → Amazon DynamoDB
- Google Directory → Looker
- Google Directory → Looker Studio
- Google Directory → Microsoft Power BI
More sources for Azure Data Lake Storage
- Google Ecommerce → Azure Data Lake Storage
- Google PageSpeed Insights → Azure Data Lake Storage
- Greenhouse → Azure Data Lake Storage
- Gridly → Azure Data Lake Storage
- Harness → Azure Data Lake Storage
- Harvest Forecast → Azure Data Lake Storage
- Heap → Azure Data Lake Storage
- Hellobaton → Azure Data Lake Storage
- Heroku → Azure Data Lake Storage
- PostgreSQL → Azure Data Lake Storage
- Hubplanner → Azure Data Lake Storage
- Impact → Azure Data Lake Storage
Early access
Connect Google Directory to Azure Data Lake Storage the easy way
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