DatriseAI-first ETL

Polygon Stock API to GoodData Integration

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

How Datrise loads Polygon Stock API into GoodData

Datrise syncs Polygon Stock API's tickers, aggregate bars, trades, quotes, splits, and dividends into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.

Ideal for embedded, multi-tenant analytics.

Endpoints

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

GoodData: Composable analytics platform with headless BI and embedded dashboards.

How Polygon Stock API entities map to GoodData

Polygon Stock API entityGoodData objectNotes
tickerspolygon_stock_api_tickersid PK · custom fields → flattened columns
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 GoodData?

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

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

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

Early access

Connect Polygon Stock API to GoodData the easy way

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