Hyperliquid 🌱

Hyperliquid data is currently in beta and the schemas are subject to change. DEX Trades:

Data is backfilled, but as of March 2025, the Hyperliquid API has a limitation so only the last 10k trades per address are available. This means that we're unable to get 100% coverage of trades for ~1% of traders (~4,000 traders). Once this is accessible, any gaps will be backfilled.

Hyperliquid is an L1 built to support an ecosystem of permisionless financial applications. The flagship native application is the Hyperliquid DEX, a fully onchain order book exchange.

Tables

Using hyperliquid.dex.trades is recommended as it enriches the raw.trades table with relevant trade & token metadata

Table Name	Description
hyperliquid.raw.trades	Raw Hyperliquid spot & perpetual trades data This is available as a real-time Kafka stream without the extra_fields column.
hyperliquid.dex.trades	Enriched Hyperliquid spot & perpetual trades data.
hyperliquid.raw.tokens	List of tokens that are traded on Hyperliquid DEX, with token metadata such as token name and symbol. Currently only includes spot tokens.
hyperliquid.assets.transfers	Token transfers on Hyperliquid L1. Currently only includes deposits & withdrawals.

Sample Queries

Get total monthly DEX volume on Hyperliquid over time

SELECT
    DATE_TRUNC('MONTH', timestamp) AS month,
    token_a_symbol,
    SUM(usd_amount) AS volume_usd
FROM hyperliquid.dex.trades
GROUP BY ALL

Get all available trades for a given user

select
    *
from hyperliquid.dex.trades
where 1=1
    and (buyer_address = <address_to_search> or seller_address = <address_to_search>)

Get all trades of BTC in the last 24 hours

select
    *
from hyperliquid.dex.trades
where 1=1
    and token_a_symbol = 'BTC'
    and timestamp >= current_timestamp - interval '24 hours'

Get a list of tokens traded in the last 24 hours, with a breakdown of spot vs perpertuals volume, ordered by total USD volume traded

select
    token_a_symbol,
    sum(case when market_type = 'spot' then usd_amount else 0 end) as total_spot_usd_amount,
    sum(case when market_type = 'perpetuals' then usd_amount else 0 end) as total_perpetuals_usd_amount,
    sum(usd_amount) as total_usd_amount,
from hyperliquid.dex.trades
where 1=1
    and timestamp >= current_timestamp - interval '24 hours'
group by all
order by total_usd_amount desc

Get daily activity metrics, aggregated by token, for the last 7 days

select
    date(timestamp) as day,
    token_a_symbol,
    count(distinct buyer_address) as num_buyers,
    count(distinct seller_address) as num_sellers,
    sum(usd_amount) as total_usd_amount,
from hyperliquid.dex.trades
where 1=1
    and timestamp >= current_timestamp - interval '7 days'
group by all
order by 1 asc

Table Columns

dex.trades

Column Name	Description
market_type	The type of market for the trade, e.g. spot, perpetuals
coin	A unique identifier for the asset being traded: • The coin for perpetuals is the standard token symbol, e.g. HYPE • The coin for spot tokens is an ID representing a pair of tokens based on Hyperliquid's metadata, e.g. @4 (coin) represents token 5/token 0, which corresponds to JEFF/USDC The metadata is available from the info endpoint of Hyperliquid's API
token_a_symbol	The symbol of the first token in the trading pair
token_b_symbol	The symbol of the second token in the trading pair. At the moment, this is always USDC
amount	The quantity of token_a being traded (normalized)
price	The execution price of token_a for the trade, in terms of token_b (usually USDC)
usd_amount	The quantity of token_a being traded, in USD terms
buyer_address	The address of the buyer in the trade
seller_address	The address of the seller in the trade
timestamp	The UTC timestamp of when the trade was executed
transaction_hash	The transaction hash for the trade. There can be multiple trades (i.e. multiple records with different trade_id) for the same transaction_hash
trade_id	An identifier for the trade. Some historical trades share a tid of 0
unique_id	A unique identifier for each trade
extra_fields	Additional information for each trade. See notes for more details.

raw.trades

Column Name	Description
coin	A unique identifier for the asset being traded: • The coin for perpetuals is the standard token symbol, e.g. HYPE • The coin for spot tokens is an ID representing a pair of tokens based on Hyperliquid's metadata, e.g. @4 (coin) represents token 5/token 0, which corresponds to JEFF/USDC The metadata is available from the info endpoint of Hyperliquid's API
price	Price of the coin at the time of the trade
side	B = Buy (spot) / Long (perpetuals) A = Sell (spot) / Short (perpetuals)
size	Units of the coin that were traded
users	An array of 2 users that were involved in the trade
transaction_hash	The transaction hash for the trade
trade_id	An identifier for the trade. Some historical trades share a tid of 0
timestamp	The UTC timestamp of when the trade was executed
unique_id	A unique identifier for each trade
extra_fields	Additional information for each trade. See notes for more details.

Notes

extra_fields

The extra_fields column contains additional information for each trade including fees and liquidation details. Some caveats to be aware of:

• New trades are first fetched from Hyperliquid Websocket API, so the extra_fields are initially unavailable. We attempt to refetch all new trades via the Info endpoint, to source the extra_fields. Given the 10k transaction limit on the API, it's possible that some trades cannot be refetched.

• Because of the above, trades may have:

  • extra_fields not populated with buyer or seller details: this means the trade could not be backfilled with additional information. These can be identified by extra_fields:source = 'api.hyperliquid.xyz/ws'

  • extra_fields populated with one of the buyer or seller details: we were able to backfill details for one side of the trade (i.e. the buy side or sell side)

  • extra_fields populated with both buyer and seller details: we were able to backfill details for both sides of the trade

Sample on extra_fields

{
  "buyer": {
    "builder_fee": null,
    "closed_pnl": "0.0",
    "crossed": true,
    "dir": "Open Long",
    "fee": "0.0",
    "fee_token": "USDC",
    "liquidation": null,
    "order_id": 80667495079,
    "start_position": "99492.0"
  },
  "seller": {
    "builder_fee": null,
    "closed_pnl": "0.0",
    "crossed": false,
    "dir": "Open Short",
    "fee": "0.0",
    "fee_token": "USDC",
    "liquidation": null,
    "order_id": 80667490005,
    "start_position": "-361760.0"
  },
  "source": "api.hyperliquid.xyz/info"
}

trade_id & unique_id

In most cases, the trade_id can be thought of as the unique identifier for a trade. However, there are cases where this isn't true:

• Before 24 Nov 2023: For historical Hyperliquid trades before 24 Nov 2023, the trade_id for all trades was 0. For those trades, we construct a unique_id from other values.

• After 24 Nov 2023: There are a handful of trades where the Hyperliquid API returns the same trade_id for trades from different transactions. Because of this, we use the combination of trade_id and transaction_hash unique identifier for trades.

FAQs

Is it possible to fetch all historical trades of <address>?

The Hyperliquid API currently has a limitation, so only the last 10k trades for each address is available. If an address has made less than 10k trades as of the time of backfill (~March 2025), then all their historical trades will be available. However, fetching all historical trades is not currently possible for addresses that have done more than 10k trades. Once historical data becomes accessible, any gaps will be backfilled.

How are liquidations treated in the dex.trades table?

To find liquidations, look for any dex.trades where the HLP Liquidator (0x2e3d94f0562703b25c83308a05046ddaf9a8dd14) is either the buyer or seller address.

Hyperliquidity Provider (HLP) is a protocol vault that does market making and liquidations. The HLP Liquidator is a component strategy that's part of the HLP. As per Hyperliquid, "this strategy liquidates positions on all coins as soon as they become liquidatable. Once it acquires these positions, it exits the positions using a market making algorithm."