Real-World Assets (RWAs)

Real-world assets bring offchain value onchain: tokenized treasuries and money-market funds, tokenized equities, commodities, private credit, and real estate. Dune provides curated RWA data covering both halves of the market — tokenized RWAs, where the asset exists as a real token you can hold and transfer, and synthetic RWA perpetuals on Hyperliquid HIP-3 markets, where traders get exposure to a real-world asset without any token existing.

Maintained by: Dune · Refresh: hourly (activity) to daily (balances, NAV) · Chains: 19 — Ethereum, Arbitrum, Avalanche, Base, BNB, Ink, Mantle, Monad, Optimism, Plasma, Plume, Polygon, Robinhood Chain, Sei, zkSync, plus Solana, Aptos, Sui, XRPL, and Stellar

Explore on Dune

The RWA overview dashboard: AUM by asset class, issuer league tables, and chain distribution.

Get This Data

Access RWA data via API, Datashare, or the Dune App.

Available Data

Registry & Classification

Which assets exist, on which chains, and the product behind each one — asset class, issuer, legal wrapper, and eligibility

Holders & Supply

Daily holder balances, entity attribution, outstanding supply, and issuance flows

Valuation (NAV)

Onchain net asset value from issuer and oracle contracts, with point-in-time pricing windows

Activity & Trading

Token transfers, secondary-market trades, and RWA perpetual futures activity

All Tables

Complete inventory of all RWA tables

When to Use These Tables

Use RWA tables when you need to:

Track AUM, supply, and holder growth for tokenized treasuries, funds, and equities
Measure issuer and platform market share across asset classes
Analyze holder concentration and entity composition, including CEX and protocol holdings
Value onchain positions using issuer-published NAV rather than market price
Monitor issuance and redemption flows against issuer-reported figures
Track secondary-market liquidity for RWAs on DEXs and RWA-native venues
Compare tokenized exposure against synthetic perpetual exposure for the same underlying
Segment products by legal wrapper, custodian, regulator, or investor eligibility

Query Performance

Activity tables (transfers, trades, perp_trades) are partitioned by block_month. Always filter on it, and add blockchain when you only need one chain — Robinhood Chain and Solana dominate row counts, so unfiltered scans are expensive. balances is a daily snapshot, so filter day to a single date unless you need a trend.

-- ✅ Good: partition-pruned and chain-scoped
SELECT * FROM rwa_multichain.transfers
WHERE block_month >= DATE_TRUNC('month', CURRENT_DATE)
  AND blockchain = 'ethereum'

Methodology

Tokenized RWAs are built around rwa_multichain.tokens, the canonical registry of every tracked asset. Its token_id column normalizes each chain’s native identifier — EVM contract address, Solana mint address, Aptos asset type, Sui coin type, XRPL and Stellar asset ids — into one value, so a single query spans all 19 chains. transfers, balances, and trades all join back to it on (blockchain, token_id), and token_metadata supplies the product behind the token — asset class, issuer, platform, plus the legal wrapper, custodian, regulator, and investor eligibility. Valuation uses NAV rather than market price, because most tokenized RWAs either barely trade onchain or trade at a price pinned to NAV. nav records each onchain NAV update event; nav_intervals forward-fills those events into valid_from / valid_to windows so point-in-time pricing is a plain range join. Note that the NAV tables key on asset_address as VARBINARY, which matches token_address on the activity tables rather than token_id, so joins need a cast: '0x' || lower(to_hex(asset_address)). Synthetic RWA perpetuals use a native perp schema — side, price, size, notional, funding, open interest — not a two-token swap schema. rwa_hyperliquid.markets is the registry of curated HIP-3 markets, rwa_multichain.perp_trades holds taker-leg fills, and perp_metrics_hourly / perp_metrics_daily pre-aggregate volume, open interest, and funding. Perp fills keep the taker leg only, so volume matches Hyperliquid’s own reported figures instead of double-counting both sides, and open interest is reported both-sides (longs plus shorts) to match the Hyperliquid UI. Each half classifies exposure with the vocabulary that fits it. token_metadata uses credit, equities, commodities, cash_equivalent, real_estate, other; the Hyperliquid tables use rates, equities, credit, fx, commodities, private_funds, real_estate. equities, credit, commodities, and real_estate mean the same thing on both sides, so those compare directly — for the rest, map to whichever grouping your analysis needs. The two halves never share token identifiers: a perpetual has no token behind it, so it never joins to rwa_multichain.tokens.

Example Queries

Largest tokenized assets by AUM and holder count:

SELECT
  token_symbol,
  blockchain,
  COUNT(DISTINCT address) AS holders,
  SUM(balance_usd) AS aum_usd
FROM rwa_multichain.balances
WHERE day = CURRENT_DATE - INTERVAL '1' DAY
  AND balance > 0
GROUP BY 1, 2
ORDER BY 4 DESC NULLS LAST
LIMIT 25

Point-in-time USD value using the NAV in force on each day:

SELECT
  b.day,
  b.token_symbol,
  n.issuer,
  SUM(b.balance * n.usd_nav_price) AS aum_usd
FROM rwa_multichain.balances b
JOIN rwa_multichain.nav_intervals n
  ON n.blockchain = b.blockchain
  AND '0x' || lower(to_hex(n.asset_address)) = b.token_address
  AND b.day >= DATE(n.valid_from)
  AND (n.valid_to IS NULL OR b.day < DATE(n.valid_to))
WHERE b.day >= CURRENT_DATE - INTERVAL '30' DAY
GROUP BY 1, 2, 3
ORDER BY 1 DESC, 4 DESC

Synthetic perp volume and open interest by asset class:

SELECT
  asset_class,
  SUM(volume_usd) AS volume_usd,
  SUM(open_interest_usd) AS open_interest_usd
FROM rwa_hyperliquid.perp_metrics_daily
WHERE block_date >= CURRENT_DATE - INTERVAL '7' DAY
  AND block_date < CURRENT_DATE
GROUP BY 1
ORDER BY 2 DESC

prices.day / prices.hour — market prices for RWAs that also trade as ordinary crypto assets
tokens.transfers — all token transfers, unfiltered by RWA scope
dex.trades — full DEX trade coverage; rwa_multichain.trades is the RWA-scoped subset plus RWA-native venues

Enterprise Data Solutions

Need custom RWA datasets, additional chains, or dedicated support? Talk to our enterprise team.

Build Custom Models

Build private RWA analytics pipelines with the dbt Connector.

Curated Data

Solana

Hyperliquid

Non-EVM Networks

Protocols

EVM Networks

Partner Data

Dune Index

Real-World Assets (RWAs)

Explore on Dune

Get This Data

Available Data

Registry & Classification

Holders & Supply

Valuation (NAV)

Activity & Trading

All Tables

When to Use These Tables

Query Performance

Methodology

Example Queries

Enterprise Data Solutions

Build Custom Models

Explore on Dune

Get This Data

​Available Data

Registry & Classification

Holders & Supply

Valuation (NAV)

Activity & Trading

All Tables

​When to Use These Tables

​Query Performance

​Methodology

​Example Queries

​Related Tables

Enterprise Data Solutions

Build Custom Models

Available Data

When to Use These Tables

Query Performance

Methodology

Example Queries

Related Tables