AWS CloudTrail to Amazon S3 Data Lake Integration
AI-first ETL from AWS CloudTrail into Amazon S3 Data Lake. Governed entities, incremental sync, typed landing tables.
How Datrise loads AWS CloudTrail into Amazon S3 Data Lake
Datrise syncs AWS CloudTrail's API events, identities, resources, event sources, error codes, and request parameters into Amazon S3 Data Lake as columnar Parquet objects partitioned 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 and compacts small files on a schedule, so re-runs update only what changed. Hive-style path partitioning (entity/date) for engine-agnostic reads. A lake has no schema enforcement, so Datrise writes a schema manifest alongside the data to keep downstream engines consistent.
Ideal for an open, engine-neutral storage layer for Spark, Athena, Trino, or DuckDB.
Endpoints
AWS CloudTrail: AWS account activity and API audit logging.
Amazon S3 Data Lake: Object storage landing zone for parquet and snapshots.
How AWS CloudTrail entities map to Amazon S3 Data Lake
| AWS CloudTrail entity | Amazon S3 Data Lake 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 Amazon S3 Data Lake?
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 Amazon S3 Data Lake types.
How does the AWS CloudTrail to Amazon S3 Data Lake sync stay up to date?
It runs incrementally — Datrise uses writes new date partitions and compacts small files on a schedule.
Related pipelines
More destinations for AWS CloudTrail
- AWS CloudTrail → Azure Data Lake Storage
- 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
More sources for Amazon S3 Data Lake
- Azure Table Storage → Amazon S3 Data Lake
- Azure Blob Storage → Amazon S3 Data Lake
- Babelforce → Amazon S3 Data Lake
- BigCommerce → Amazon S3 Data Lake
- Google BigQuery → Amazon S3 Data Lake
- Branch → Amazon S3 Data Lake
- Braze → Amazon S3 Data Lake
- Bronto → Amazon S3 Data Lake
- CallRail → Amazon S3 Data Lake
- Campaign Monitor → Amazon S3 Data Lake
- Cart → Amazon S3 Data Lake
- ChartMogul → Amazon S3 Data Lake
Early access
Connect AWS CloudTrail to Amazon S3 Data Lake the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.