GitHub Webhook to Azure Data Lake Storage Integration
AI-first ETL from GitHub Webhook into Azure Data Lake Storage. Governed entities, incremental sync, typed landing tables.
How Datrise loads GitHub Webhook into Azure Data Lake Storage
Datrise syncs GitHub Webhook's push events, pull requests, issues, releases, commits, and workflow runs 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
GitHub Webhook: Repository event stream delivered by webhook.
Azure Data Lake Storage: ADLS Gen2 object storage for analytics workloads.
How GitHub Webhook entities map to Azure Data Lake Storage
| GitHub Webhook entity | Azure Data Lake Storage object | Notes |
|---|---|---|
| push events | github_webhook_push_events | ISO-8601 timestamp columns events |
| pull requests | github_webhook_pull_requests | id PK · linked to github_webhook_push_events |
| issues | github_webhook_issues | id PK · linked to github_webhook_push_events |
| releases | github_webhook_releases | id PK · linked to github_webhook_push_events |
FAQ
How does Datrise handle GitHub Webhook'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 GitHub Webhook 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
More destinations for GitHub Webhook
- GitHub Webhook → Azure Synapse
- GitHub Webhook → Spreadsheets
- GitHub Webhook → Airtable
- GitHub Webhook → CSV Files
- GitHub Webhook → MongoDB
- GitHub Webhook → Supabase
- GitHub Webhook → Neon
- GitHub Webhook → PlanetScale
- GitHub Webhook → Amazon DynamoDB
- GitHub Webhook → Looker
- GitHub Webhook → Looker Studio
- GitHub Webhook → Microsoft Power BI
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Early access
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