AWS CloudTrail to Azure Data Lake Storage Integration
AI-first ETL from AWS CloudTrail into Azure Data Lake Storage. Governed entities, incremental sync, typed landing tables.
How Datrise loads AWS CloudTrail into Azure Data Lake Storage
Datrise syncs AWS CloudTrail's API events, identities, resources, event sources, error codes, and request parameters 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
AWS CloudTrail: AWS account activity and API audit logging.
Azure Data Lake Storage: ADLS Gen2 object storage for analytics workloads.
How AWS CloudTrail entities map to Azure Data Lake Storage
| AWS CloudTrail entity | Azure Data Lake Storage object | Notes |
|---|---|---|
| API events | aws_cloudtrail_api_events | ISO-8601 timestamp columns events |
| identities | aws_cloudtrail_identities | id PK · linked to aws_cloudtrail_api_events |
| resources | aws_cloudtrail_resources | id PK · linked to aws_cloudtrail_api_events |
| event sources | aws_cloudtrail_event_sources | ISO-8601 timestamp columns events |
FAQ
How does Datrise handle AWS CloudTrail'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 AWS CloudTrail 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 AWS CloudTrail
- AWS CloudTrail → Azure Synapse
- AWS CloudTrail → Spreadsheets
- AWS CloudTrail → Airtable
- AWS CloudTrail → CSV Files
- AWS CloudTrail → MongoDB
- AWS CloudTrail → Supabase
- AWS CloudTrail → Neon
- AWS CloudTrail → PlanetScale
- AWS CloudTrail → Amazon DynamoDB
- AWS CloudTrail → Looker
- AWS CloudTrail → Looker Studio
- AWS CloudTrail → Microsoft Power BI
More sources for Azure Data Lake Storage
- Azure Table Storage → Azure Data Lake Storage
- Azure Blob Storage → Azure Data Lake Storage
- Babelforce → Azure Data Lake Storage
- BigCommerce → Azure Data Lake Storage
- Google BigQuery → Azure Data Lake Storage
- Branch → Azure Data Lake Storage
- Braze → Azure Data Lake Storage
- Bronto → Azure Data Lake Storage
- CallRail → Azure Data Lake Storage
- Campaign Monitor → Azure Data Lake Storage
- Cart → Azure Data Lake Storage
- ChartMogul → Azure Data Lake Storage
Early access
Connect AWS CloudTrail to Azure Data Lake Storage the easy way
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