DatriseAI-first ETL

Yotpo Azure Data Lake Storage

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

How Datrise loads Yotpo into Azure Data Lake Storage

Datrise syncs Yotpo's reviews, loyalty members, redemptions, and campaign 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

Yotpo: Reviews and loyalty marketing for e-commerce brands.

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

How Yotpo entities map to Azure Data Lake Storage

Yotpo entityAzure Data Lake Storage objectNotes
reviewsyotpo_reviewsid PK · custom fields → nested struct/map fields in Parquet
loyalty membersyotpo_loyalty_membersid PK · linked to yotpo_reviews
redemptionsyotpo_redemptionsid PK · linked to yotpo_reviews
campaign eventsyotpo_campaign_eventsISO-8601 timestamp columns events

FAQ

How does Datrise handle Yotpo'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 Yotpo 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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