Six-feed Hyperliquid stack. Direct from Tokyo. No blocks in the path.
In a hyper-fast decentralized market, an enormous amount of order book activity happens between block confirmations. Order placements, cancellations, amendments, liquidity pulls, and executions can occur long before a block is finalized.
CoinAPI does not stream by block. We deliver raw, unaggregated Hyperliquid L4 order and trade mutations in real time, and complement them with oracle, TWAP, and raw node event feeds over the same WS DS source.
We don't throttle, sample, aggregate, or wait for blocks to bundle data.
Every single order placement, modification, cancellation, rejection, partial fill, and execution is streamed instantly as it occurs.
For latency-sensitive strategies, waiting for blocks means observing history. CoinAPI delivers the market as it evolves.
Hyperliquid's consensus engine lives in Tokyo, Japan.
CoinAPI captures the feed directly from the source and hot-routes L4 data to customers with minimal infrastructure hops.
The result is a cleaner latency profile, lower propagation delay, and faster visibility into order book changes across the network.
Consume low-latency live feeds through dedicated WebSocket DS infrastructure and access historical Hyperliquid L4 datasets through hourly refreshed CSV.gz flat files hosted on AWS S3.
Both delivery methods use aligned field naming conventions and symbol identifiers, while preserving format-specific message envelopes.
No data model conversions. No separate ingestion logic. No code rewrites when moving from backtesting to production.
Connect once to the dedicated Hyperliquid WS DS endpoint and subscribe to order book, trade, oracle, TWAP, misc, and system feeds in a single session.
This design reduces integration complexity and keeps all Hyperliquid real-time streams in one transport channel with aligned identifiers.
Teams can start from `book_l4` and `trade_l4`, then progressively enable enrichment and raw event feeds as analytics requirements grow.
Symbol-level streams (`book_l4`, `trade_l4`, `hl_oracle_prices`, `hl_twap_statuses`) map naturally to pair-level processing and strategy engines.
Exchange-level streams (`hl_misc_events`, `hl_system_events`) deliver block-linked raw envelopes designed for observability and audit workflows.
The split lets you optimize high-frequency symbol pipelines separately from lower-frequency exchange event consumers.
CoinAPI exposes both real-time WebSocket DS streams and historical flat files for Hyperliquid with aligned field naming conventions.
Research and production systems can share schema contracts and validation logic instead of maintaining separate data adapters.
This reduces model drift risk and speeds up deployment cycles for quant and execution teams.
Most cryptocurrency market data feeds aggregate liquidity into price levels, hiding the actual mechanics of the matching engine. Level 4 (L4) data is different.
L4 is an unaggregated, individual order stream where every resting order is treated as a unique entity. Instead of seeing total volume at a price level, you see the actual orders that create that liquidity.
Each order can be tracked throughout its complete lifecycle:
Every passive resting order and trade match includes the public Ethereum or Hyperliquid wallet address associated with the participant.
Unique exchange-assigned order IDs allow traders to follow specific orders throughout their lifecycle.
CoinAPI exposes detailed order metadata including:
Understanding the differences between market data tiers helps explain why professional trading firms increasingly rely on Level 4 feeds.
| Data Depth | Structural Granularity | Core Metadata Visible | Primary Technical Use Case | Network Profile |
|---|---|---|---|---|
| Level 1 (L1) | Top of Book | Best Bid/Ask (BBO) | Portfolio valuation, chart rendering, retail trading | Ultra-Low |
| Level 2 (L2) | Aggregated Depth | Volume grouped by price level | Liquidity mapping, execution routing | Low to Medium |
| Level 3 (L3) | Individual Queue | Separate orders without participant attribution | Queue modeling, order arrival analysis | High |
| Level 4 (L4) | Full Flow & Identity | Individual orders, wallet addresses, lifecycle updates, maker/taker attribution | HFT, market making, whale tracking, order flow analysis, microstructure research | Ultra-High |
Level 4 provides the closest possible representation of the matching engine and exposes the information hidden by aggregated order book feeds.
Use one endpoint with multiple feed families and align downstream consumers by data scope and latency profile.
| Feed | Scope | Emission Unit | Core Data Surface | Typical Consumer |
|---|---|---|---|---|
| book_l4 | symbol-scoped | Per trading pair | Order-level resting liquidity, order lifecycle, bracket relationships | Microstructure, queue reconstruction, execution simulation |
| trade_l4 | symbol-scoped | Per trading pair | Executed trades with taker/maker wallet attribution | Order flow analysis, participant behavior, toxic-flow detection |
| hl_oracle_prices | symbol/coin-scoped | Per coin update | Oracle/mark/external perp prices, daily refs, input components, update class | Risk controls, divergence monitoring, funding and liquidation modeling |
| hl_twap_statuses | symbol/coin-scoped | Per TWAP id | TWAP lifecycle and progress fields (status, executed size/notional, flags) | Execution monitoring, quality benchmarking, TWAP analytics |
| hl_misc_events | exchange-scoped | Per exchange event | Raw event envelope with block number, event type, JSON payload | Audit pipelines, low-level event observability, custom parsers |
| hl_system_events | exchange-scoped | Per exchange event | Raw system action envelope with block number, action type, JSON payload | System-action tracking, controls and policy monitoring |
Symbol-scoped feeds are optimized for strategy and execution pipelines. Exchange-scoped feeds are optimized for observability, audit, and custom event processing.
Production data captured across the Hyperliquid ecosystem highlights why unaggregated L4 data is required to understand market behavior.
Approximately 88% of all submitted orders result in an immediate rejection event, often from aggressive Add Liquidity Only strategies.
Of the orders that successfully reach the book, approximately 98.9% are eventually canceled.
Only around 1.1% of submitted orders ultimately result in a completed fill.
Real-Time WebSocket DS Stream — a dedicated low-latency endpoint:
wss://hyperliquidl4.ws-ds.md.coinapi.io/
Use symbol filters for symbol-scoped feeds (`book_l4`, `trade_l4`, `hl_oracle_prices`, `hl_twap_statuses`). Exchange-level feeds (`hl_misc_events`, `hl_system_events`) can also be consumed without symbol filters.
{
"type": "hello",
"heartbeat": false,
"subscribe_data_type": [
"book_l4",
"trade_l4",
"hl_oracle_prices",
"hl_twap_statuses",
"hl_misc_events",
"hl_system_events"
],
"subscribe_filter_symbol_id": [
"HYPERLIQUIDL4_PERP_BTC_USDC",
"HYPERLIQUIDL4_PERP_ETH_USDC",
"HYPERLIQUIDL4_SPOT_SOL_USDC"
],
"subscribe_update_limit_ms_quote": 0
}Full Level 4 order book snapshots and incremental updates. An initial snapshot is delivered upon subscription, followed by continuous incremental updates.
Executed Hyperliquid transactions with participant attribution for sophisticated order flow analysis and counterparty research.
Per-coin oracle and mark price enrichment stream with daily references and source input components.
TWAP lifecycle stream with execution progress, completion states, and execution attributes.
Exchange-level raw misc event stream normalized into envelope fields for low-level observability.
Exchange-level raw system event stream with block-linked metadata and original payloads.
Level 4 data enables analysis that is impossible with traditional Level 1 and Level 2 feeds — a direct view into how liquidity actually behaves rather than how it appears after aggregation.
Because CoinAPI provides both real-time and historical datasets, teams can build, test, and deploy strategies using a single data source throughout the entire development lifecycle.
Beyond classic L4 reconstruction, oracle, TWAP, and raw event streams unlock richer execution intelligence and cross-signal diagnostics.
Use the WebSocket DS Hyperliquid documentation for message contracts, enums, and integration examples across all six feed families.
Instead of reconstructing market activity after the fact, CoinAPI exposes every order placement, modification, cancellation, partial fill, and execution with the highest level of transparency available on Hyperliquid.
The result is a single platform for capturing, storing, researching, and deploying strategies based on the most granular Hyperliquid market data available.