Raw

The hypercore dataset holds the standardized HyperCore tables. HyperCore is an exchange rather than a general-purpose chain, so where an EVM chain publishes logs and internal calls, HyperCore publishes the streams its matching engine emits: what filled, what was ordered, how the book moved, and what funding was settled.

Tables

Table	Since	Description
`blocks`	2025-07	One row per block, with the number of records each stream emitted in it.
`node_trades`	2025-03	One row per fill, in a slim shape: the account, market, side, price, size and whether the account crossed the spread.
`node_fills`	2025-07	One row per fill, in the full shape: the fee and the token it was paid in, the builder credited, the position direction and the liquidation fields where the fill closed a position.
`node_fills_without_block_number`	2025-05 to 2025-07	The fills the node recorded before block numbers were attached to them, in the same shape as `node_fills`.
`node_funding`	2025-09	One row per market per funding settlement, with the rate it applied and the amount settled on each side.
`events`	2025-09	One row per exchange event outside trading, typed by `event_kind` and, for ledger updates, by `ledger_type`.
`orders`	2025-11	One row per order status change, with the limit price, the size, the order type and the time in force.
`book`	2025-11	One row per change to a resting order level, with the price and the level size before and after.
`twap`	2025-11	One row per state change of a TWAP order, with the size and notional executed so far.
`writer_actions`	2025-12	One row per action written into HyperCore from HyperEVM, such as a spot send or a delegation, with the EVM transaction that sent it.

Blocks are keyed on block_number, fills on trade_id together with the account and side, orders and TWAPs on order_id and twap_id, and funding on the market and settlement time. coin is the market symbol as the venue lists it, and it is the join back to the market registries on Perpetuals. Three columns hold JSON, because their shape depends on a type column: event_json in events, children in orders and action in writer_actions. Read the type column first, then extract the fields that type defines.

Sample queries

Every table splits by day on block_timestamp. Bound it in every query and keep it bare on the left of the comparison; wrapping it in a function reads every partition. book and orders hold every resting-order change and every order state change, so they are the two largest tables here: bound them to a single day.

Daily trading
Busiest markets
Funding settlements

Count daily fills and the accounts behind them. node_trades is the slim fill stream, so it answers volume and participation questions at the lowest cost.

select
    timestamp_trunc(block_timestamp, day) as day,
    count(*) as fills,
    count(distinct account_address) as accounts
from `hypercore.node_trades`
where block_timestamp >= timestamp('2026-08-16')
  and block_timestamp < timestamp('2026-08-23')
group by day
order by day

Rank markets by notional traded on one day, with the fees they produced. A fill’s notional is its price times its size, and both are BIGNUMERIC, so the multiplication stays exact.

select
    coin,
    count(*) as fills,
    sum(price * size) as notional,
    sum(fee) as fees
from `hypercore.node_fills`
where block_timestamp >= timestamp('2026-08-20')
  and block_timestamp < timestamp('2026-08-21')
group by coin
order by notional desc
limit 20

Read the funding paid on each market over one week. funding_rate is the rate the settlement applied, and the long and short amount columns split the settled amount by the side of the position.

select
    coin,
    count(*) as settlements,
    avg(funding_rate) as average_rate,
    sum(long_funding_amount) as long_amount,
    sum(short_funding_amount) as short_amount
from `hypercore.node_funding`
where block_timestamp >= timestamp('2026-08-16')
  and block_timestamp < timestamp('2026-08-23')
group by coin
order by abs(sum(total_funding_amount)) desc
limit 20

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Sample queries