ForceManager → Azure Data Lake Storage
AI-first ETL from ForceManager into Azure Data Lake Storage. Governed entities, incremental sync, typed landing tables.
How Datrise loads ForceManager into Azure Data Lake Storage
Datrise syncs ForceManager's contacts, accounts, deals, activities, and lifecycle events 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
ForceManager: European CRM for SMB and mid-market sales teams.
Azure Data Lake Storage: ADLS Gen2 object storage for analytics workloads.
How ForceManager entities map to Azure Data Lake Storage
| ForceManager entity | Azure Data Lake Storage object | Notes |
|---|---|---|
| contacts | forcemanager_contacts | id PK · custom fields → nested struct/map fields in Parquet |
| accounts | forcemanager_accounts | id PK · linked to forcemanager_contacts |
| deals | forcemanager_deals | id PK · linked to forcemanager_contacts |
| activities | forcemanager_activities | ISO-8601 timestamp columns events |
FAQ
How does Datrise handle ForceManager'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 ForceManager 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 ForceManager
- ForceManager → Azure Synapse
- ForceManager → Spreadsheets
- ForceManager → Airtable
- ForceManager → CSV Files
- ForceManager → MongoDB
- ForceManager → Supabase
- ForceManager → Neon
- ForceManager → PlanetScale
- ForceManager → Amazon DynamoDB
- ForceManager → Looker
- ForceManager → Looker Studio
- ForceManager → Microsoft Power BI
More sources for Azure Data Lake Storage
- SUMA CRM → Azure Data Lake Storage
- Efficy CRM → Azure Data Lake Storage
- Sellsy → Azure Data Lake Storage
- Teamleader → Azure Data Lake Storage
- SuperOffice CRM → Azure Data Lake Storage
- Sage CRM → Azure Data Lake Storage
- Vincle → Azure Data Lake Storage
- Help Scout → Azure Data Lake Storage
- HubSpot Service Hub → Azure Data Lake Storage
- Chorus.ai → Azure Data Lake Storage
- Brevo → Azure Data Lake Storage
- GetResponse → Azure Data Lake Storage
Early access
Connect ForceManager to Azure Data Lake Storage the easy way
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