DatriseAI-first ETL

VinSolutions to Azure Data Lake Storage Integration

AI-first ETL from VinSolutions into Azure Data Lake Storage. Governed entities, incremental sync, typed landing tables.

How Datrise loads VinSolutions into Azure Data Lake Storage

Datrise syncs VinSolutions's leads, customers, vehicles, deals, appointments, and service records 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

VinSolutions: Dealer CRM tied to inventory and equity mining.

Azure Data Lake Storage: ADLS Gen2 object storage for analytics workloads.

How VinSolutions entities map to Azure Data Lake Storage

VinSolutions entityAzure Data Lake Storage objectNotes
leadsvinsolutions_leadsid PK · custom fields → nested struct/map fields in Parquet
customersvinsolutions_customersid PK · linked to vinsolutions_leads
vehiclesvinsolutions_vehiclesid PK · linked to vinsolutions_leads
dealsvinsolutions_dealsid PK · linked to vinsolutions_leads

FAQ

How does Datrise handle VinSolutions'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 VinSolutions 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

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