DatriseAI-first ETL

Persistiq to Azure Data Lake Storage Integration

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

How Datrise loads Persistiq into Azure Data Lake Storage

Datrise syncs Persistiq's prospects, campaigns, sequences, email events, users, and dispositions 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

Persistiq: Outbound sales sequences and prospect tracking.

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

How Persistiq entities map to Azure Data Lake Storage

Persistiq entityAzure Data Lake Storage objectNotes
prospectspersistiq_prospectsid PK · custom fields → nested struct/map fields in Parquet
campaignspersistiq_campaignsid PK · linked to persistiq_prospects
sequencespersistiq_sequencesid PK · linked to persistiq_prospects
email eventspersistiq_email_eventsISO-8601 timestamp columns events

FAQ

How does Datrise handle Persistiq'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 Persistiq 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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