20+ chains. USD-enriched tables. Real-time protocol analytics.
Track whale flows, build DeFi income statements, compare tokenized asset yields, and monitor governance health. All in SQL, all crosschain. Your analysts stop stitching data and start finding alpha.
The assets your team evaluates trade 24/7 on transparent ledgers. Protocol revenue, user growth, liquidity shifts, governance activity -- it's all onchain, updated every block. But most investment workflows still run on fragmented data, manual queries, and reports that are stale before they're published.
Your analysts spend too much time stitching data together from five platforms. They should be spending it finding alpha.
01 / The Flipside approach
Tables across 20+ chains with USD pricing, entity labels, and crosschain normalization already applied. Query them directly, or set up agents that alert you when something moves.
Pre-built ez_ tables with decimal adjustments, USD conversions, and entity labels already joined. No raw hex parsing. No building your own pricing layer. Clean SQL that returns investment signals.
Agents monitor whale movements, track protocol metrics, and ping your team on material changes. Alerts go to Slack, email, or automated briefings on whatever schedule you set.
Unified crosschain.* views let you compare metrics across Ethereum, Solana, Arbitrum, Base, and every major ecosystem without managing separate data pipelines for each.
02 / Use cases
Six research workflows, each backed by real tables you can query today.
Key signal:
"Exchange deposits spiked 4x in 6 hours — selling pressure incoming?"
Key signal:
"TVL up 40% but active users flat — is this real growth or mercenary capital?"
Key signal:
"Volume on Base DEXs tripled this week — which protocols are gaining share?"
Key signal:
"Which tokenized treasury product has the best risk-adjusted yield right now?"
Key signal:
"Governance participation dropped 60% — is this project losing its community?"
Key signal:
"$200M bridged to Arbitrum this week — is this the start of a migration?"
03 / The data layer
Exchange flow analysis, protocol income statements, and TVL trends. Standard SQL against clean tables with USD values and entity labels pre-joined.
Explore the full schemaInflows vs. outflows as a positioning signal
Join transfer tables with dim_labels to classify every large movement by counterparty type. Exchange deposit spikes signal selling pressure. Withdrawal surges signal accumulation. The labels do the classification for you.
-- 30-day exchange net flows for ETH
SELECT
DATE_TRUNC('day', block_timestamp) AS date,
SUM(CASE WHEN l.label_type = 'cex'
AND l.address = t.to_address
THEN amount_usd ELSE 0 END) AS inflows_usd,
SUM(CASE WHEN l.label_type = 'cex'
AND l.address = t.from_address
THEN amount_usd ELSE 0 END) AS outflows_usd
FROM ethereum.core.ez_native_transfers t
JOIN ethereum.core.dim_labels l
ON l.address IN (t.from_address, t.to_address)
WHERE block_timestamp >= CURRENT_DATE - 30
GROUP BY 1 ORDER BY 1Market share and trader counts per protocol
Every swap across every major DEX, normalized into a single table with platform attribution, token metadata, and USD amounts. Aggregate at any granularity or filter down to individual whale trades.
-- DEX volume by platform, last 30 days
SELECT
DATE_TRUNC('day', block_timestamp) AS date,
platform,
COUNT(*) AS swap_count,
COUNT(DISTINCT sender) AS unique_traders,
SUM(amount_in_usd) AS total_volume_usd
FROM ethereum.defi.ez_dex_swaps
WHERE block_timestamp >= CURRENT_DATE - 30
AND amount_in_usd IS NOT NULL
GROUP BY 1, 2
ORDER BY 1 DESC, 5 DESCDeFi income statement components, updated daily
Think of TVL as a balance sheet proxy and lending activity as the revenue line. Liquidation events tell you when a protocol is under stress. Interest rate OHLC data shows yield trends. Put them together and you have a DeFi income statement that updates hourly, not quarterly.
-- Protocol TVL with 7-day trend
SELECT
platform, blockchain,
tvl_usd,
tvl_usd - LAG(tvl_usd, 7) OVER (
PARTITION BY platform, blockchain
ORDER BY block_date
) AS tvl_change_7d
FROM crosschain.defi.ez_protocol_tvl
WHERE block_date = CURRENT_DATE - 1
ORDER BY tvl_usd DESC04 / Agent intelligence
Set up agents that run your investment queries on a schedule. When something material changes, they ping you on Slack or email. You configure the thresholds; they do the watching.
Alerts fire when large holders start accumulating or distributing, when whale-to-exchange transfers spike, or when a known fund opens a position in a token you're watching.
Weekly briefings on TVL trends, user growth, lending rates, and governance activity for your portfolio protocols. Flags material changes like TVL drops, liquidation spikes, or participation declines.
Daily or weekly updates comparing yields across tokenized treasury and credit products. Alerts when a product's APY changes materially or when holder concentration shifts above your threshold.
Tracks bridge flows across 14+ chains and flags when a chain starts gaining or losing capital at unusual rates. These shifts tend to show up in bridge data before they show up in price.
05 / Tokenized assets
Flipside integrates RWA.xyz data directly into the same SQL environment you use for DeFi and onchain analysis. That means 65 timeseries metrics across 16 asset classes, queryable alongside every other Flipside table. Compare BlackRock BUIDL against Franklin Templeton or Apollo ACRED on identical metrics without switching tools.
65 metrics per token
Supply, yields, lending, transfers, holder concentration, bridge activity
16 asset classes
US Treasury Debt, Private Credit, Stablecoins, Real Estate, Corporate Bonds, and more
Dashboard-ready views
Pre-joined ez_ tables with NAV, APY, yield-to-maturity, and price history
-- Compare tokenized treasury yields
SELECT
asset_name, ticker, issuer_name,
value AS apy_7_day
FROM external.gold.rwa_xyz__ez_assets
WHERE measure_slug = 'apy_7_day'
AND asset_class_name IN (
'US Treasury Debt',
'U.S. Treasury Debt')
QUALIFY ROW_NUMBER() OVER (
PARTITION BY asset_id
ORDER BY date DESC
) = 1
ORDER BY apy_7_day DESC06 / Chain coverage
| Category | Chains |
|---|---|
| EVM L1s | Ethereum, BSC, Avalanche, Gnosis |
| EVM L2s / Rollups | Polygon, Arbitrum, Optimism, Base, Ink, Monad, Somnia |
| Non-EVM | Solana, Bitcoin, NEAR, SUI, Flow, Cosmos, Axelar, Canton, Aptos |
| Crosschain | Unified crosschain.* views spanning all EVM chains |
07 / Who uses this
Quantitative strategies, whale flow signals, and protocol due diligence with onchain data.
Token due diligence, protocol health scoring, and portfolio monitoring across chains.
Tokenized asset comparison, yield analysis, and institutional-grade RWA analytics.
Crosschain capital flow analysis, governance research, and market structure studies.
20+
Chains with investment data
700M+
Labeled addresses for counterparty ID
Hourly
Protocol metrics refresh
5
Governance chains covered
Flipside covers 20+ chains with pre-built tables for protocol TVL, DEX swaps, lending activity (deposits, borrows, liquidations, interest rates), native and token transfers with USD values, entity labels for counterparty identification, hourly pricing, and crosschain bridge activity. Decimal adjustments and USD conversions come pre-applied, so queries return investment-ready numbers without additional transformation.
Yes. Join ez_native_transfers or ez_token_transfers (both include USD amounts) with dim_labels to classify each counterparty as an exchange, fund, protocol, or known wallet. From there you can track exchange net flows, whale-to-whale transfers, and accumulation patterns. These tend to be leading indicators for positioning.
Flipside integrates RWA.xyz data with 65 timeseries metrics across 16 asset classes, all queryable in SQL. You can track NAV, 7-day and 30-day APY, yield-to-maturity, holder concentration, mint/burn patterns, and bridge activity for products like BlackRock BUIDL, Franklin Templeton, and Apollo ACRED. The data lives in the external.gold.rwa_xyz schema alongside all other Flipside tables.
Join four table families: ez_protocol_tvl for the balance sheet (TVL over time), ez_dex_swaps for trading fee revenue, ez_lending_borrows and ez_lending_deposits for interest income, and ez_core_metrics_hourly for user growth. The result is a protocol-level income statement that refreshes hourly rather than quarterly.
Yes. Governance voting data is available across Solana (Realms and Tribeca), Cosmos Hub, Axelar, ENS DAO, and Canton. You can track proposal frequency, voter turnout, and participation trends as onchain proxies for project health. Think of it as corporate governance metrics, but updated with every block rather than every quarter.
Bridge activity tables cover 14+ chains and show where capital is moving before it shows up in price. You can track which chains are gaining or losing capital, which bridge protocols carry the most volume, and whether bridge inflows actually correlate with DEX activity and TVL growth on the destination chain.
Get Started
20+ chains of investment-ready data, 700M+ labeled addresses, and AI agents that watch your portfolio around the clock. Tell us what you're researching and we'll show you the tables.