Polygon Stock API to Amazon S3 Data Lake Integration
AI-first ETL from Polygon Stock API into Amazon S3 Data Lake. Governed entities, incremental sync, typed landing tables.
How Datrise loads Polygon Stock API into Amazon S3 Data Lake
Datrise syncs Polygon Stock API's tickers, aggregate bars, trades, quotes, splits, and dividends 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
Polygon Stock API: Equities market data, trades, and aggregates.
Amazon S3 Data Lake: Object storage landing zone for parquet and snapshots.
How Polygon Stock API entities map to Amazon S3 Data Lake
| Polygon Stock API entity | Amazon S3 Data Lake object | Notes |
|---|---|---|
| tickers | polygon_stock_api_tickers | id PK · custom fields → nested struct/map fields in Parquet |
| aggregate bars | polygon_stock_api_aggregate_bars | id PK · linked to polygon_stock_api_tickers |
| trades | polygon_stock_api_trades | id PK · linked to polygon_stock_api_tickers |
| quotes | polygon_stock_api_quotes | id PK · linked to polygon_stock_api_tickers |
FAQ
How does Datrise handle Polygon Stock API'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 Polygon Stock API 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 Polygon Stock API
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- Polygon Stock API → Looker Studio
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Early access
Connect Polygon Stock API to Amazon S3 Data Lake the easy way
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