Data source
Data from IGDB, delivered clean.
1 dataset pulled from IGDB's releases, checked field by field and shipped the way you want them — daily, weekly, or hourly, your call.
- 1 dataset
- 1 industry
- Real rows on request
What Datadory delivers from IGDB
1IGDB API (Twitch/Amazon)
Pick a catch, see the rows.
Name any IGDB dataset and we send real rows from it — not a screenshot of rows. 1,744 datasets. Pick your catch.
Get a sampleAPI, files, or your warehouse. Daily, weekly, or hourly.
Straight answers about IGDB data
How big is the IGDB database?
Tens of millions of rows across more than sixty relational entity types - games, companies, platforms, franchises, release dates and media assets among them. The source publishes no per-entity totals, so Datadory reports exact counts in every delivery rather than a rounded headline.
What makes IGDB data relational?
About half the columns on a game record are typed identifier arrays pointing at other entity types: companies resolve to developer and publisher rows, platforms to platform families, release_dates to regional dates, external_games to storefront listings, similar_games to neighbors. Analysis becomes keyed joins, not re-collection.
Whose ratings sit on an IGDB game record?
Two independent families: `rating`/`rating_count` aggregates IGDB user sentiment while `aggregated_rating`/`aggregated_rating_count` compiles external critic scores, and `hypes` counts pre-release follows. Weighting audience response, critical consensus and anticipation separately is possible because they never blend.
Can IGDB data support forward-looking analysis?
Yes. Announced-but-unreleased titles hold rows already, carrying `first_release_date`, pre-release `hypes` and age-rating entries, so launch calendars, anticipation tracking and pipeline diligence all run on the same schema as the historical archive.