TVL, trading volume, lending activity, user behavior. Across 20+ chains.
Query any DeFi protocol with SQL. Pre-aggregated tables for fast answers, granular event data when you need depth. AI agents watch your metrics and ping Slack when something moves.
01 / What you can track
The same SQL schema works across protocols and chains. Learn it once, query everything.
Key question:
"Is Aave growing or losing ground to Morpho this quarter?"
Key question:
"Which DEX is winning volume on Base this month?"
Key question:
"Where are liquidation risks building right now?"
Key question:
"How much USDC is sitting in DEX pools vs. lending pools?"
Key question:
"Which L2 is gaining the most DeFi users this quarter?"
Key question:
"How many unique voters participated in the last 12 months?"
02 / The data layer
Pre-aggregated stats tables for fast dashboards. Granular event tables when you need to trace individual swaps. Same schema across every chain.
Explore the schemaFast queries, no heavy aggregation
Daily metrics already rolled up and ready to chart. TVL by protocol, DEX volume by chain, bridge flows, stablecoin transfers, active addresses. These are the tables you'll use 80% of the time.
-- TVL for top 10 protocols, last 90 days
SELECT block_date, platform, SUM(balance_usd) AS tvl
FROM crosschain.defi.ez_protocol_tvl
WHERE block_date >= CURRENT_DATE - 90
GROUP BY 1, 2 ORDER BY 1Every swap, borrow, liquidation, and bridge event
When you need to trace individual transactions, filter by wallet, or build custom aggregations. Every event includes USD values, token metadata, and protocol labels.
-- DEX market share by protocol, last 30 days
SELECT platform, SUM(amount_in_usd) AS volume
FROM crosschain.defi.ez_dex_swaps
WHERE block_timestamp >= CURRENT_DATE - 30
GROUP BY 1 ORDER BY volume DESCKnow who's behind the address
700M+ labeled addresses. Join any DeFi event with dim_labels to see if the trader is a whale, a CEX, a bot, or a first-time user. Temporal tags track wallet behavior changes over time.
-- Whale trading volume on Uniswap v3
SELECT s.block_timestamp::DATE, SUM(s.amount_in_usd)
FROM ethereum.defi.ez_dex_swaps s
JOIN ethereum.core.dim_labels l ON s.origin_from_address = l.address
WHERE l.label_type = 'whale'
AND s.platform = 'uniswap-v3'
GROUP BY 1 ORDER BY 103 / Agent intelligence
Set up AI agents that run queries on a schedule, detect anomalies, and deliver findings to Slack or email. No dashboards to refresh. No alerts to configure in five different tools.
Get pinged when a protocol's TVL drops more than 10% in a day, when a large LP exits a pool, or when a competitor's TVL crosses yours.
Track specific wallets or labeled whale cohorts. Know when they accumulate, dump, or move assets to a new protocol before it shows up on CT.
Agents flag spikes in liquidation volume, unusual flash loan activity, or lending utilization rates crossing thresholds you set.
Weekly summaries comparing your protocol's metrics against competitors. Market share shifts, user migration patterns, and new deployments on chains you care about.
04 / Who uses this
Track protocol health, user growth, and competitive positioning across chains.
Token due diligence, whale tracking, and market intelligence for portfolio decisions.
Ecosystem metrics, developer activity, and DeFi TVL tracking for reporting and grants.
Sector analysis, protocol benchmarking, and data for published reports and threads.
20+
Chains covered
100+
DEXs and protocols decoded
700M+
Labeled addresses
7T+
Rows of data
TVL by protocol and chain, DEX trading volume and market share, lending borrow/supply rates, liquidation events, stablecoin supply and flows, bridge volumes, governance participation, and wallet-level behavior. All metrics are available via SQL on pre-aggregated tables or granular event-level data across 20+ chains.
Flipside covers every major DEX including Uniswap, Raydium, Jupiter, Orca, Curve, PancakeSwap, and dozens more via normalized ez_dex_swaps tables. Lending coverage includes Aave, Compound, Euler, Morpho, and others with borrows, deposits, repayments, liquidations, and interest rate data in ez_lending_ tables.
Yes. Flipside's crosschain schema normalizes data across 20+ chains so you can compare TVL, volume, users, and fees with a single SQL query. Pre-aggregated tables like ez_tvl_protocol_metrics_daily and ez_dex_protocol_metrics_daily include day-over-day and 90-day comparisons built in.
AI agents run scheduled and event-driven queries against your protocol data, then deliver summaries and alerts to Slack, email, or webhooks. Agents can monitor TVL drops, whale exits, liquidation spikes, governance votes, and competitive shifts without anyone checking a dashboard.
fact_ tables contain cleaned, typed event-level data. ez_ tables join that data with prices, labels, and metadata so you get USD values and decoded fields out of the box. Start with ez_ tables for faster queries. Use fact_ tables when you need raw granularity.
Data is indexed within minutes of onchain confirmation. Pre-aggregated daily stats tables report through the most recent complete day. Historical coverage goes back to genesis block for all supported chains.
Get Started
20+ chains, 100+ decoded protocols, pre-aggregated stats tables. Tell us what you're tracking and we'll show you how fast you can get answers.