Google Sheets → Azure Data Lake Storage
AI-first ETL from Google Sheets into Azure Data Lake Storage. Governed entities, incremental sync, typed landing tables.
How Datrise loads Google Sheets into Azure Data Lake Storage
Datrise syncs Google Sheets's spreadsheet-based CRM rows, updates, and operational workflow tables 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 Sheets: Spreadsheet CRM workflows and lightweight pipelines.
Azure Data Lake Storage: ADLS Gen2 object storage for analytics workloads.
How Google Sheets entities map to Azure Data Lake Storage
| Google Sheets entity | Azure Data Lake Storage object | Notes |
|---|---|---|
| spreadsheet-based CRM rows | google_sheets_spreadsheet_based_crm_rows | id PK · custom fields → nested struct/map fields in Parquet |
| updates | google_sheets_updates | id PK · linked to google_sheets_spreadsheet_based_crm_rows |
| operational workflow tables | google_sheets_operational_workflow_tables | id PK · linked to google_sheets_spreadsheet_based_crm_rows |
FAQ
How does Datrise handle Google Sheets'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 Sheets 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 Sheets
- Google Sheets → Azure Synapse
- Google Sheets → Spreadsheets
- Google Sheets → Airtable
- Google Sheets → CSV Files
- Google Sheets → MongoDB
- Google Sheets → Supabase
- Google Sheets → Neon
- Google Sheets → PlanetScale
- Google Sheets → Amazon DynamoDB
- Google Sheets → Looker
- Google Sheets → Looker Studio
- Google Sheets → Microsoft Power BI
More sources for Azure Data Lake Storage
- Close → Azure Data Lake Storage
- Nimble → Azure Data Lake Storage
- ActiveCampaign → Azure Data Lake Storage
- ClickUp → Azure Data Lake Storage
- Google Ads → Azure Data Lake Storage
- Google Analytics → Azure Data Lake Storage
- Twitter/X Ads → Azure Data Lake Storage
- LinkedIn Ads → Azure Data Lake Storage
- Meta Ads → Azure Data Lake Storage
- SAP → Azure Data Lake Storage
- Amplitude → Azure Data Lake Storage
- MoEngage → Azure Data Lake Storage
Early access
Connect Google Sheets to Azure Data Lake Storage the easy way
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