Ripple

ripple holds the standardized XRP Ledger tables. The XRP Ledger calls its blocks ledgers, and they land in blocks. Transactions land in transactions, which is wide: it has a column for every field any kind of transaction can carry, and only the ones that apply to that kind are filled in. Everything a transaction changed lands in affected_nodes.

Tables

Table	Since	Description
`blocks`	2013-01	One row per ledger, with close times and total XRP in existence.
`transactions`	2013-01	One row per transaction, with the columns its `transaction_type` populates.
`affected_nodes`	2013-01	One row per ledger entry a transaction created, modified or deleted.

Ledgers are keyed on number and transactions on transaction_hash. Each affected_nodes row carries new_fields, final_fields and previous_fields as JSON, so you can see what a record held before the change and after it. The columns that hold amounts, amount, deliver_max and delivered_amount, are JSON rather than numbers. An amount on this chain is one of two things: a plain count of drops if it is XRP, one drop being a millionth of an XRP, or a small record naming the currency, its issuer and the value if it is anything else. For payments, read delivered_amount: it says what arrived, which is not always what was asked for, because the chain allows a payment to deliver less than its stated amount.

Sample queries

Transaction success rate
Tokenized assets ranked
Priced tokens

Count transactions by type and their success rate on one day. tesSUCCESS is the result code of a successful transaction.

select
    transaction_type,
    count(*) as transactions,
    countif(transaction_result = 'tesSUCCESS') as successful
from `ripple.transactions`
where block_timestamp >= timestamp('2026-08-20')
  and block_timestamp < timestamp('2026-08-21')
group by transaction_type
order by transactions desc

Rank the tokenized assets issued on the XRP Ledger by circulating market cap.

select
    assets.symbol,
    assets.asset_type,
    daily.market_cap_circulating_total
from `metrics_asset_tokens.market_cap_circulating_total_daily` as daily
join `dimensions.asset_tokens` as deployments
    using (asset_token_id)
join `dimensions.assets` as assets
    using (asset_id)
where daily.timestamp >= timestamp('2026-08-22')
  and daily.timestamp < timestamp('2026-08-23')
  and deployments.chain_id = 'ripple'
order by daily.market_cap_circulating_total desc
limit 20

List the XRP Ledger tokens that carried a daily price over one week.

with priced as (
    select
        token_id,
        avg(price) as avg_price,
        count(*) as price_days
    from `metrics_tokens.price_daily`
    where timestamp >= timestamp('2026-08-16')
      and timestamp < timestamp('2026-08-23')
      and chain_id = 'ripple'
    group by token_id
)

select
    tokens.symbol,
    tokens.name,
    priced.avg_price,
    priced.price_days
from priced
join `dimensions.tokens` as tokens using (token_id)
order by priced.avg_price desc
limit 20

Notes

Above the raw tables sits the rest of the catalog, and the XRP Ledger shows up in two parts of it: the tokenized assets issued on it, and the list of tokens we know about with the daily prices they carry. Tokenized funds, stablecoins and tokenized commodities make up the asset side. No app or trading-pool table covers the chain. The market pages go deeper on each of these. Stablecoins and Tokenized assets cover the tokenized assets and their daily tables. Tokens covers the token list and the daily price table.

Overview

Core entities

Core datasets

Market verticals

Chain verticals

Tables

Sample queries

Notes

​Tables

​Sample queries

​Notes

Tables

Sample queries

Notes