DatriseAI-first ETL

Polygon Stock API to MongoDB Integration

AI-first ETL from Polygon Stock API into MongoDB. Governed entities, incremental sync, typed landing tables.

How Datrise loads Polygon Stock API into MongoDB

Datrise syncs Polygon Stock API's tickers, aggregate bars, trades, quotes, splits, and dividends into MongoDB as a collection per source entity. Flexible or custom fields land in native nested documents, and timestamps such as created, updated, and status changes are typed as BSON Date.

Sync is incremental: Datrise uses upserts by stable id with updateOne(upsert) on the source primary key, so re-runs update only what changed. Optional sharding on the entity id for large collections. Mongo has no fixed schema, so Datrise keeps field types consistent across documents to avoid mixed-type query surprises.

Ideal for document-oriented apps that want CRM data in their existing Mongo store.

Endpoints

Polygon Stock API: Equities market data, trades, and aggregates.

MongoDB: Document database for flexible schemas.

How Polygon Stock API entities map to MongoDB

Polygon Stock API entityMongoDB objectNotes
tickerspolygon_stock_api_tickersid PK · custom fields → native nested documents
aggregate barspolygon_stock_api_aggregate_barsid PK · linked to polygon_stock_api_tickers
tradespolygon_stock_api_tradesid PK · linked to polygon_stock_api_tickers
quotespolygon_stock_api_quotesid PK · linked to polygon_stock_api_tickers

FAQ

How does Datrise handle Polygon Stock API's custom fields in MongoDB?

Flexible values are stored as native nested documents, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native MongoDB types.

How does the Polygon Stock API to MongoDB sync stay up to date?

It runs incrementally — Datrise uses upserts by stable id with updateOne(upsert) on the source primary key.

Related pipelines

Early access

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