DatriseAI-first ETL

Confluence to Azure Data Lake Storage Integration

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

How Datrise loads Confluence into Azure Data Lake Storage

Datrise syncs Confluence's spaces, pages, blog posts, comments, attachments, and page versions 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

Confluence: Team wiki and documentation workspace.

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

How Confluence entities map to Azure Data Lake Storage

Confluence entityAzure Data Lake Storage objectNotes
spacesconfluence_spacesid PK · custom fields → nested struct/map fields in Parquet
pagesconfluence_pagesid PK · linked to confluence_spaces
blog postsconfluence_blog_postsid PK · linked to confluence_spaces
commentsconfluence_commentsid PK · linked to confluence_spaces

FAQ

How does Datrise handle Confluence'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 Confluence 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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