DatriseAI-first ETL

RD Station CRM Azure Data Lake Storage

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

How Datrise loads RD Station CRM into Azure Data Lake Storage

Datrise syncs RD Station CRM'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

RD Station CRM: CRM widely used in Latin America for sales pipeline and customer ops.

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

How RD Station CRM entities map to Azure Data Lake Storage

RD Station CRM entityAzure Data Lake Storage objectNotes
contactsrd_station_crm_contactsid PK · custom fields → nested struct/map fields in Parquet
accountsrd_station_crm_accountsid PK · linked to rd_station_crm_contacts
dealsrd_station_crm_dealsid PK · linked to rd_station_crm_contacts
activitiesrd_station_crm_activitiesISO-8601 timestamp columns events

FAQ

How does Datrise handle RD Station CRM'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 RD Station CRM 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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