Parquet File to Amazon S3 Data Lake Integration
AI-first ETL from Parquet File into Amazon S3 Data Lake. Governed entities, incremental sync, typed landing tables.
How Datrise loads Parquet File into Amazon S3 Data Lake
Datrise syncs Parquet File's row groups, columns, schemas, partitions, file batches, and column statistics 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
Parquet File: Columnar Parquet files from lakes and exports.
Amazon S3 Data Lake: Object storage landing zone for parquet and snapshots.
How Parquet File entities map to Amazon S3 Data Lake
| Parquet File entity | Amazon S3 Data Lake object | Notes |
|---|---|---|
| row groups | parquet_file_row_groups | id PK · custom fields → nested struct/map fields in Parquet |
| columns | parquet_file_columns | id PK · linked to parquet_file_row_groups |
| schemas | parquet_file_schemas | id PK · linked to parquet_file_row_groups |
| partitions | parquet_file_partitions | id PK · linked to parquet_file_row_groups |
FAQ
How does Datrise handle Parquet File'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 Parquet File 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 Parquet File
- Parquet File → Azure Data Lake Storage
- Parquet File → Azure Synapse
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- Parquet File → Looker
- Parquet File → Looker Studio
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Early access
Connect Parquet File 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.