Perpetuals

HyperCore runs two kinds of market and the Perpetuals band documents both. A perpetual market is a contract that tracks a price and never expires, such as BTC Perpetual. An order-book market is a cash market where the token itself changes hands through a book of resting orders, such as the HYPE/USDC spot book or an outcome market. Each kind has its own registry, its own daily tables and its own trade table.

dimensions.perp_markets and dimensions.order_book_markets: one row per market.
metrics_perp_markets and metrics_order_book_markets: one table per measure, one row per market per day. metrics_perp_market_tokens and metrics_order_book_market_tokens split a market by the token it settles or quotes in.
facts_perp_markets.trades, facts_perp_markets.liquidations and facts_order_book_markets.trades: one row per fill.

A perpetual market credits two apps. exchange_app_id is the venue whose matching engine settled the trade, and interface_app_id is the builder the market is listed under. The two hold the same value on a venue’s own markets and differ on a builder-deployed HIP-3 market, where hyperliquid-perps is the engine. An order-book market runs under a single app and has one app_id where a perpetual market has the pair. The money tables on both kinds have chain_id, project_id and app_id, so a HyperCore filter reads straight off them. The perpetual position and trader tables, such as open_interest_daily and funding_rate_daily, key on perp_market_id alone, so filter those through dimensions.perp_markets. Every column is documented at Perpetuals.

Sample queries

Top perpetual markets
Open interest and funding
Top order books
HIP-3 markets

Rank HyperCore perpetual markets by the notional settled on one day. The exchange lens credits the matching engine, so it totals the venue’s own markets and the HIP-3 markets it settles for builders in one figure.

select
    markets.name,
    markets.interface_app_id,
    sum(daily.notional_trading_volume) as notional_trading_volume
from `metrics_perp_markets.exchange_notional_trading_volume_daily` as daily
join `dimensions.perp_markets` as markets
    using (perp_market_id)
where daily.timestamp >= timestamp('2026-08-20')
  and daily.timestamp < timestamp('2026-08-21')
  and daily.chain_id = 'hypercore'
group by markets.name, markets.interface_app_id
order by notional_trading_volume desc
limit 20

Follow one perpetual market’s open interest and funding rate day by day. Both tables key on perp_market_id alone, so the market identifier is the whole filter.

select
    positions.timestamp,
    positions.open_interest,
    funding.funding_rate
from `metrics_perp_markets.open_interest_daily` as positions
join `metrics_perp_markets.funding_rate_daily` as funding
    using (timestamp, perp_market_id)
where positions.timestamp >= timestamp('2026-08-16')
  and positions.timestamp < timestamp('2026-08-23')
  and positions.perp_market_id = 'hlbtc-hypercore'
order by positions.timestamp

Rank the HyperCore order books by the value traded over one week. Every book here quotes in a dollar stablecoin, so the volume figure is already a dollar figure.

select
    markets.name,
    markets.app_id,
    sum(daily.trading_volume) as trading_volume
from `metrics_order_book_markets.trading_volume_daily` as daily
join `dimensions.order_book_markets` as markets
    using (order_book_market_id)
where daily.timestamp >= timestamp('2026-08-16')
  and daily.timestamp < timestamp('2026-08-23')
  and daily.chain_id = 'hypercore'
group by markets.name, markets.app_id
order by trading_volume desc
limit 20

Find the HyperCore markets a builder deployed rather than the venue, and the fees they produced. A HIP-3 market is one where the matching engine and the listing builder are different apps, so comparing the two credit columns separates them.

select
    markets.name,
    markets.interface_app_id,
    sum(daily.fees) as fees
from `metrics_perp_markets.fees_daily` as daily
join `dimensions.perp_markets` as markets
    using (perp_market_id)
where daily.timestamp >= timestamp('2026-08-16')
  and daily.timestamp < timestamp('2026-08-23')
  and daily.chain_id = 'hypercore'
  and markets.exchange_app_id != markets.interface_app_id
group by markets.name, markets.interface_app_id
order by fees desc
limit 20

Overview

Popular datasets

Market verticals

Chain ecosystems

Core entities

Sample queries

​Sample queries

Sample queries