Metrics

An app is one deployed version of a protocol: uniswap-v3 is an app of the Uniswap project. The same measures are carried per app and per app and chain, one row per day. Each measure is its own table, holding the level’s identifier columns, timestamp, and one value column. Every measure is in USD unless it counts something, and a missing row means no figure for that day, not zero. The project levels above live at Projects ▸ Metrics.

Tables

App
App × chain

One row per (app_id, timestamp) in every metrics_apps table, since 2020-05. Each row also carries project_id. Details such as which market sectors the app belongs to live in dimensions.apps.

Table	Value column	What it holds
`metrics_apps.tvl_daily`	`tvl`	Value locked in the app’s contracts at day end, in USD.
`metrics_apps.trading_volume_daily`	`trading_volume`	Cash value of the trades that took place on the app, in USD.
`metrics_apps.active_loans_daily`	`active_loans`	Value of loans outstanding on the app at day end, in USD.
`metrics_apps.assets_staked_daily`	`assets_staked`	Value staked on the app at day end, in USD.
`metrics_apps.fees_daily`	`fees`	Fees paid by users of the app, in USD.
`metrics_apps.fees_supply_side_daily`	`fees_supply_side`	The part of those fees the app passed on to the supply side, in USD.
`metrics_apps.revenue_daily`	`revenue`	Fees the app kept, in USD.
`metrics_apps.token_incentives_daily`	`token_incentives`	Value of the project’s own token paid out as rewards through the app, in USD.
`metrics_apps.outstanding_supply_daily`	`outstanding_supply`	Stablecoin supply outstanding today attributed to this app, in USD. Apps of stablecoin issuers only.
`metrics_apps.user_dau_daily`	`user_dau`	Distinct addresses that used the app that day. A HyperLogLog estimate.
`metrics_apps.user_wau_daily`	`user_wau`	Distinct addresses that used the app in the trailing 7 days. A HyperLogLog estimate.
`metrics_apps.user_mau_daily`	`user_mau`	Distinct addresses that used the app in the trailing 30 days. A HyperLogLog estimate.

One row per (app_id, chain_id, timestamp) in every metrics_app_chains table, since 2020-05: the narrowest level published. Each row also carries project_id.

Table	Value column	What it holds
`metrics_app_chains.tvl_daily`	`tvl`	Value locked in the app’s contracts on the chain at day end, in USD.
`metrics_app_chains.trading_volume_daily`	`trading_volume`	Cash value of the trades that took place on the app and chain, in USD.
`metrics_app_chains.active_loans_daily`	`active_loans`	Value of loans outstanding on the app and chain at day end, in USD.
`metrics_app_chains.fees_daily`	`fees`	Fees paid by users of the app on the chain, in USD.
`metrics_app_chains.fees_supply_side_daily`	`fees_supply_side`	The part of those fees the app passed on to the supply side on the chain, in USD.
`metrics_app_chains.revenue_daily`	`revenue`	Fees the app kept on the chain, in USD.

Sample queries

App
App × chain
Apps of one project

Rank apps by fees over one week.

select
    app_id,
    sum(fees) as fees
from `metrics_apps.fees_daily`
where timestamp >= timestamp('2026-08-01')
  and timestamp < timestamp('2026-08-08')
group by app_id
order by fees desc

Split one app’s fees by chain over one week. Dropping the chain filter and grouping by chain turns the narrowest table into a comparison across every chain the app runs on.

select
    chain_id,
    sum(fees) as fees
from `metrics_app_chains.fees_daily`
where app_id = 'uniswap-v3'
  and timestamp >= timestamp('2026-08-01')
  and timestamp < timestamp('2026-08-08')
group by chain_id
order by fees desc

Compare the apps one project runs by fees over one week. The registry supplies the name; the daily table supplies the figure.

select
    apps.app_id,
    apps.name,
    sum(daily.fees) as fees
from `metrics_apps.fees_daily` as daily
join `dimensions.apps` as apps
    using (app_id)
where daily.project_id = 'hyperliquid'
  and daily.timestamp >= timestamp('2026-08-01')
  and daily.timestamp < timestamp('2026-08-08')
group by apps.app_id, apps.name
order by fees desc

Notes

Measures live in separate tables, so a query for two of them is a join on the level’s identifier columns and timestamp. Use full join when both measures matter: a day can carry TVL and no fees, and an inner join would drop it. trading_volume, fees, revenue and token_incentives measure a day’s activity and add up freely: a weekly figure is seven daily rows added together, and an app figure is its chain rows added together. tvl, active_loans and assets_staked are values standing at day end, so a weekly figure for them is a choice of day rather than a sum. Counts of distinct addresses never add up at all: user_dau is counted at the app level, so a user active on two chains counts once. An app figure rolls into its project’s on Projects ▸ Metrics. Metric definitions holds the rule for every measure as data you can query.

Overview

Core entities

Core datasets

Market verticals

Chain verticals

Tables

Sample queries

Notes

​Tables

​Sample queries

​Notes

Tables

Sample queries

Notes