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: 20 — Ethereum, Arbitrum, Avalanche, Base, BNB, Ink, Mantle, Monad, Optimism, Plasma, Plume, Polygon, Robinhood Chain, Sei, zkSync, plus Solana, Aptos, Sui, XRPL, and Stellar

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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

Token-unit USD prices for AUM, plus onchain NAV events and point-in-time 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 curated USD prices (NAV-backed where an oracle exists)
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 identity registry of every tracked asset. token_id already stores each chain’s native identifier as VARCHAR — EVM contract address, Solana mint address, Aptos asset type, Sui coin type, XRPL and Stellar asset ids — so a single query spans all 20 chains. Join transfers, balances, and supply on (blockchain, token_id). Classification and legal attributes live one layer up: tokens_reference_data is one row per token per chain (join activity on (blockchain, token_id), join balances_enriched on token_product_id), and product_reference_data is one row per product_id. There is no rwa_multichain.token_metadata table. trades has no token_id; resolve the RWA leg with rwa_side plus token_bought_address / token_sold_address. Valuation uses rwa_multichain.prices for AUM. That table is USD per on-chain token unit with [valid_from, valid_to) windows, and supply.supply_usd is already supply * prices.price_usd. nav still records each onchain NAV update; nav_intervals forward-fills those events. The 0x + to_hex(asset_address) join against token_address is EVM-only. For Solana, Stellar, and XRPL, asset_address is UTF-8-encoded token_id, not an EVM address. Prefer prices for cross-chain point-in-time valuation. 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_hyperliquid.perp_trades holds taker-leg fills with per-fill trader leverage and margin mode, 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. Metrics unique keys use (block_month, block_hour|block_date, perp_dex, market_symbol), not coin. perp_metrics_daily is daily grain, hourly refresh. Tokenized products and Hyperliquid markets share the same legal asset-class vocabulary: credit, fixed_income, cash_equivalent, equities, multi_asset, commodities, real_estate, fx, other. On token rows that vocabulary is product_asset_class (and product_reference_data.asset_class); tokens_reference_data.asset_class is a separate title-case token-list vocab. 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 price in force on each day:

SELECT
  b.day,
  b.token_symbol,
  r.issuer_name,
  SUM(b.balance * p.price_usd) AS aum_usd
FROM rwa_multichain.balances AS b
INNER JOIN rwa_multichain.prices AS p
  ON p.blockchain = b.blockchain
  AND p.token_id = b.token_id
  AND CAST(b.day AS TIMESTAMP) >= p.valid_from
  AND (p.valid_to IS NULL OR CAST(b.day AS TIMESTAMP) < p.valid_to)
LEFT JOIN rwa_multichain.tokens_reference_data AS r
  ON r.blockchain = b.blockchain
  AND r.token_id = b.token_id
WHERE b.day >= CURRENT_DATE - INTERVAL '30' DAY
GROUP BY 1, 2, 3
ORDER BY 1 DESC, 4 DESC

Synthetic perp volume by asset class (do not sum open interest across days):

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 '1' DAY
GROUP BY 1
ORDER BY 2 DESC

Summing open_interest_usd across markets on a single day is valid. Summing it across days is not: open interest is a stock, not a flow.

rwa_multichain.prices — curated USD per token unit; the AUM join used by supply.supply_usd
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.

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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

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

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