Metrics

DEX metrics are two daily tables. metrics.dex_pools_daily holds one row per pool per day, with every pool measure. metrics.dex_pool_pairs_daily splits the same volume by traded pair: one row per pool per pair per day. Every figure is in USD, converted with our token prices at the finest level and added up from there.

metrics.dex_pools_daily: one row per pool per day.
metrics.dex_pool_pairs_daily: one row per pool per traded pair per day.

Tables

Pool
Pair

One row per pool per day, keyed (dex_pool_id, timestamp). The table carries trading_volume, tvl, fees and flash_loan_volume, alongside the keys for the app, the protocol version, the project and the chain.

Column	Type	Description
`timestamp`	`TIMESTAMP`	Day the row aggregates, truncated to UTC midnight.
`dex_pool_id`	`STRING`	Pool the row measures, keyed like `dimensions.dex_pools`.
`deployment_id`	`STRING`	The operating app’s deployment on the pool’s chain.
`protocol_id`	`STRING`	The app operating the pool.
`project_id`	`STRING`	Project the operating app belongs to.
`chain_id`	`STRING`	Chain the pool lives on.
`trading_volume`	`BIGNUMERIC`	USD value of the day’s swaps in the pool.
`tvl`	`BIGNUMERIC`	Total value locked: the USD value of what the pool was holding at the end of the day.
`fees`	`BIGNUMERIC`	USD value of the day’s swap and flash-loan fees.
`flash_loan_volume`	`BIGNUMERIC`	USD value of the day’s flash loans drawn from the pool.

One row per pool per traded pair per day, keyed (dex_pool_id, dex_pair_id, timestamp). dex_pair_id is the two token addresses in sorted order joined with the chain, so the pair’s two tokens are readable from the key itself and need no columns of their own.

Column	Type	Description
`timestamp`	`TIMESTAMP`	Day the row aggregates, truncated to UTC midnight.
`dex_pool_id`	`STRING`	Pool the volume executed in.
`dex_pair_id`	`STRING`	The two tokens that traded: their addresses in sorted order, joined with the chain.
`project_id`	`STRING`	Project the operating app belongs to.
`app_id`	`STRING`	The app operating the pool, read from the pool registry table.
`chain_id`	`STRING`	Chain the pool lives on.
`trading_volume`	`BIGNUMERIC`	USD value of the day’s swaps in this pool between this pair.

Sample queries

Read one pool’s daily series.

select
    timestamp,
    trading_volume,
    tvl,
    fees,
    flash_loan_volume
from `metrics.dex_pools_daily`
where dex_pool_id = '0x88e6a0c2ddd26feeb64f039a2c41296fcb3f5640-ethereum'
  and timestamp >= timestamp('2026-06-01')
order by timestamp

fees is worked out from the same volume figure as trading_volume, so dividing one by the other gives back the pool’s fee rate. It is not a second, independent measurement of what traders paid. Pool rows add up cleanly to the app’s deployment on that chain, then the protocol version, then the project, because every level uses the same token prices.

Rank pools by trading volume on one day.

select
    dex_pool_id,
    protocol_id,
    chain_id,
    trading_volume,
    tvl,
    fees
from `metrics.dex_pools_daily`
where timestamp = timestamp('2026-08-01')
  and trading_volume is not null
order by trading_volume desc
limit 25

Total one pair’s volume across every pool that trades it. The same pair can trade in many pools, and it carries the same dex_pair_id in all of them, so a total across pools is a group by on that column.

select
    timestamp,
    sum(trading_volume) as trading_volume
from `metrics.dex_pool_pairs_daily`
where dex_pair_id = '0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48-0xc02aaa39b223fe8d0a0e5c4f27ead9083c756cc2-ethereum'
  and timestamp >= timestamp('2026-08-01')
group by timestamp
order by timestamp

Break one pool’s volume down by pair. A pool’s pair rows add back up to its row on the pool table. A breakdown by single token would not: every swap involves two tokens, so counting it under each one counts it twice and the total stops matching the pool.

select
    dex_pair_id,
    sum(trading_volume) as trading_volume
from `metrics.dex_pool_pairs_daily`
where dex_pool_id = '0x88e6a0c2ddd26feeb64f039a2c41296fcb3f5640-ethereum'
  and timestamp >= timestamp('2026-08-01')
  and timestamp < timestamp('2026-08-08')
group by dex_pair_id
order by trading_volume desc

Sum the exchange sector’s daily volume and fees. There is no table holding the DEX sector as a single daily series: this groups the daily pool table, joined to dimensions.projects, by day. Check membership with in unnest(...) as below, or filter on primary_market_sector, where every project appears exactly once; grouping by the raw market_sectors list with unnest in the from clause counts a project once per sector it carries.

select
    panel.timestamp,
    sum(panel.trading_volume) as sector_volume,
    sum(panel.fees) as sector_fees
from `metrics.dex_pools_daily` as panel
join `dimensions.projects` as projects
    on projects.project_id = panel.project_id
where 'exchange' in unnest(projects.market_sectors)
  and panel.timestamp >= timestamp('2026-08-01')
group by panel.timestamp
order by panel.timestamp

Check a pool’s volume against the sum of its pairs. The pool row is the sum of its pair rows rather than a second, separate measurement, so on any day the pool traded the two sides agree exactly.

select
    pools.timestamp,
    pools.trading_volume as pool_grain,
    pairs.summed as pair_grain
from `metrics.dex_pools_daily` as pools
join (
    select
        dex_pool_id,
        timestamp,
        sum(trading_volume) as summed
    from `metrics.dex_pool_pairs_daily`
    where timestamp >= timestamp('2026-08-01')
    group by dex_pool_id, timestamp
) as pairs
    using (dex_pool_id, timestamp)
where pools.dex_pool_id = '0x88e6a0c2ddd26feeb64f039a2c41296fcb3f5640-ethereum'
  and pools.timestamp >= timestamp('2026-08-01')
order by pools.timestamp

Notes

Amounts add up: volume, fees and flash-loan volume are dollar figures, so a total across pools or days means something. Counts of distinct traders do not. One address that traded in five pools is one trader, but adding those five pools’ daily counts makes it five. A trader count for anything wider than one pool on one day has to be worked out from the addresses themselves.

Overview

Core entities

Market verticals

Chain verticals

Tables

Sample queries

Notes

​Tables

​Sample queries

​Notes

Tables

Sample queries

Notes