Interest rates - Token Terminal Docs

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facts.lending_market_interest_rates combines the rate updates of every lending protocol we decode into one table: one row per rate update in a lending market. The market’s contract emits its new rates whenever its balance of deposits and borrows changes. lending_market_id keys each row to its market in the Registry.

Columns

Column	Type	Description
`block_timestamp`	`TIMESTAMP`	Time of the block containing the update. Partition column.
`block_number`	`INT64`	Number of the block containing the update.
`transaction_hash`	`STRING`	Hash of the transaction that emitted the update.
`log_index`	`INT64`	Position of the update event in the block.
`unique_id`	`INT64`	Row key: fingerprint of `chain_id`, `block_number`, `transaction_hash`, `log_index`.
`chain_id`	`STRING`	Chain the market runs on.
`lending_market_id`	`STRING`	Market the rates belong to; joins `dimensions.lending_markets`.
`project_id`	`STRING`	Protocol operating the market, such as `aave`.
`token_id`	`STRING`	Underlying token of the market: `{token_address}-{chain_id}`.
`deposit_rate`	`FLOAT64`	Annual rate paid to depositors, as a fraction.
`borrow_rate`	`FLOAT64`	Annual rate charged to borrowers, as a fraction.

Sample queries

The table is partitioned on block_timestamp. Bound that column in every query; without a bound the query reads the whole table.

Latest rates
Rate history

Read the latest rates of every market in one protocol.

select
    markets.market_name,
    markets.chain_id,
    rates.deposit_rate,
    rates.borrow_rate
from `facts.lending_market_interest_rates` as rates
join `dimensions.lending_markets` as markets
    using (lending_market_id)
where markets.project_id = 'spark'
  and rates.block_timestamp >= timestamp('2026-08-20')
qualify row_number() over (
    partition by rates.lending_market_id
    order by rates.block_timestamp desc
) = 1
order by rates.deposit_rate desc

Read one market’s daily average rates over a month.

select
    timestamp_trunc(rates.block_timestamp, day) as day,
    avg(rates.deposit_rate) as deposit_rate,
    avg(rates.borrow_rate) as borrow_rate
from `facts.lending_market_interest_rates` as rates
join `dimensions.lending_markets` as markets
    using (lending_market_id)
where markets.project_id = 'aave'
  and markets.underlying_symbol = 'WETH'
  and markets.chain_id = 'ethereum'
  and rates.block_timestamp >= timestamp('2026-08-01')
  and rates.block_timestamp < timestamp('2026-09-01')
group by day
order by day

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