Hyperliquid Historical Data Indexer
Perpetual trading history since July 2025 - 3.13B fills with nanosecond block timing, liquidation and TWAP context - in a SQL-queryable ClickHouse warehouse.
- Direct ClickHouse SQL over history since 2025-07-27
- Fills · liquidations · TWAP, nanosecond block timing
- Builder codes, priority gas, maker/taker flag
- Per-wallet: positions · PnL · win-rate
- All perp markets, real-time refresh
- Order-level book archive on request
- Timestamp precision
- nanosecond block time
- History since
- 2025-07-27
- Fills indexed
- 3.13B (225.58 GB)
- Coverage
- all perpetual markets, real-time refresh
- Interfaces
- ClickHouse SQL + custom REST
- Order-book archive
- order-level, on request
- Database name
- hyperliquid
- Access
- credentials provisioned via Telegram
What does the Hyperliquid indexer contain?
Perpetual trading data since 27 July 2025: 3.13 billion fills across all perpetual markets, each with execution price, size, position before the fill, realized PnL, fee, builder code, TWAP membership and the full liquidation triple. Block timing is nanosecond-resolution for latency and order-flow analysis. Funding rates are not part of this dataset.
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 Historical Data Indexer.
Set up over Telegram with an engineer — endpoint, token, tuning.