[ SUPANODE ]by hightower
// hyperliquid · indexer

Hyperliquid Indexer

Complete perpetual trading history — every fill, funding payment, and TWAP with nanosecond precision — in a SQL-queryable ClickHouse warehouse.

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Hyperliquid · indexer● live
timestamp
ns
markets
all
01.WHAT'S INCLUDED// Hyperliquid · indexer
  • Direct ClickHouse SQL over full history
  • Fills · funding · TWAP, nanosecond timestamps
  • Per-wallet: positions · PnL · win-rate
  • All perp markets, real-time refresh
  • Custom REST endpoints on request
// factsSPEC
Timestamp precision
nanosecond per fill
Coverage
all perpetual markets, real-time refresh
Interfaces
ClickHouse SQL + custom REST
Database name
hyperliquid
Access
credentials provisioned via Telegram
see the full product overview →
02.HOW IT WORKS// query it like a database
query.sqlclickhouse · hyperliquid
1SELECT wallet, SUM(size) AS vol
2FROM hyperliquid.fills
3WHERE ts > now() - INTERVAL 1 HOUR
4GROUP BY wallet
5ORDER BY vol DESC LIMIT 20
→ 200 OK · 82ms · joins, CTEs, window fns
// HOW TO QUERY
Connect with any ClickHouse client — DBeaver, DataGrip, psql, or the Python client — against the hyperliquid database, then write SQL with joins, CTEs, and window functions.
// INTERFACES
Direct ClickHouse SQL, or a custom REST endpoint shaped to a recurring query (quoted per scope).
// SCHEMA
Tables, column types, and example queries live in the indexer docs.
03.FAQ// 5 questions
What does the Hyperliquid indexer contain?

Complete perpetual trading data: every fill, funding payment, and TWAP execution across all perpetual markets, with entry/exit price, position size, realized PnL, and liquidation flags. Each fill carries a nanosecond timestamp for latency and order-flow analysis.

How do I query it?

Through direct ClickHouse SQL using clients like DBeaver, DataGrip, or psql against the `hyperliquid` database. Supanode can also build a custom REST endpoint around a specific query on request.

How is access provisioned?

Connection details — host, port, username, password — are provisioned per customer over Telegram. The indexer is a flat monthly subscription.

Can I analyze individual wallets and build leaderboards?

Yes — fills are queryable per wallet, so positions, realized PnL, and win-rate roll up with plain SQL. Trader leaderboards, copy-trading research, and smart-money screens are the most common workloads on this dataset.

Why do nanosecond timestamps matter?

They preserve the exact ordering of fills, which is what order-flow analysis, latency studies, and execution backtests depend on. At second or millisecond precision, simultaneous fills collapse together and the sequencing information is gone.

Get Hyperliquid Indexer.

Set up over Telegram with an engineer — endpoint, allowlist, tuning.

[ talk to us ]◀ Hyperliquid services