Race Feed
An experimental data-ingest pipeline Remiam built for a racing-data client. A live feed of horse and dog racing data streams into a local Nuxt service, normalised and sorted into a local SQLite store, then surfaced as cleanly-structured content their live platform can consume.
The brief, the build, and the result.
Race Feed is the experimental data-ingest pipeline Remiam built for a racing-data platform client in 2025. The brief: take a live feed of horse and dog racing data — runners, odds, going, course conditions, in-race events — and turn it into something the client's live platform could read cleanly. Remiam built a local Nuxt 3 service that subscribes to the feed, processes each update on arrival, normalises the heterogeneous payloads into a consistent shape, sorts and de-duplicates the data, and persists everything into a local SQLite database structured for downstream querying. The result is a stable, queryable surface — runners separated from races, results separated from odds, in-race events queued for replay — that the client's production platform reads from. Designed as an experimental MVP to prove the ingest model end-to-end before committing to a production architecture.
- 01Subscribes to a live racing data feed (horse + dog)
- 02Processes and normalises each update on arrival
- 03Sorts and de-duplicates into clean, structured tables
- 04Persists to a local SQLite database for fast queries
- 05Structured output surface read by the client's live platform
- 06Experimental MVP — designed to prove the model before production scale-up
- 07Local Nuxt 3 service, runnable on-premise alongside the live platform