Data that reconciles to the chain.
Clean, exact, attributed historical datasets, bulk-exported in the formats your tooling already reads.
The parts you keep working around.
Float-rounded datasets produce backtests that don't reconcile to the chain.
Anonymized data forecloses whole research directions: cohorts, behavior, flow.
Vendor exports arrive in bespoke formats that need a parser before they need a model.
How the platform answers, point by point.
One schema, exact bytes, your formats.
The archive row and the live message are the same record. Hover a field. Exports land in your bucket in the formats your tooling already reads.
Archive row · trades dataset
query API · Parquet / CSV / JSONL exports
Live message · StreamSwaps
stream.hyperliquidrpc.com:443 · gRPC
Hover a field. It is the same field, byte for byte, on both sides. Backtest on the archive, deploy on the stream, change nothing.
Query first, export when sure.
SQL-style queries against the archive return JSON or CSV, so you can size the dataset before you pull it. Bulk exports ship as Parquet, CSV, or JSONL.
Read the docs# Query the archive directly; results as JSON or CSVcurl https://data.hyperliquidrpc.com/query \ -H 'x-api-key: YOUR_KEY' \ -d "SELECT coin, count() AS fills, sum(toFloat64(sz) * toFloat64(px)) AS notional FROM trades WHERE block_time > now() - 86400 GROUP BY coin ORDER BY notional DESC LIMIT 20"The plan that fits.
Ultra
$199/moRecommendedFull archive, replay, and maximum throughput.
Ultra includes full query access and a 250 GB/mo export quota. Large one-time exports and custom backfills are quoted separately; contact us with the range.
Compare both plansPull a sample before you commit.
Pro includes full query access and a monthly export quota. Large one-time backfills are quoted separately. Contact us with the range.