Query DeFi, bridges, wallets, and protocol data across all 11 chains
11+ blockchains. 95+ tables. Standardized schemas.
Flipside's crosschain database pulls data from 11 blockchains into standardized Snowflake schemas. Your team queries DeFi activity, token flows, wallet behavior, and protocol performance across Ethereum, Solana, Arbitrum, Base, and more without switching databases or learning new conventions.
Query DeFi, bridges, wallets, and protocol data across all 11 chains
01 / The Problem
Every blockchain has its own schema, naming conventions, and data model. Comparing DEX volume on Ethereum vs. Solana means writing separate queries against separate databases, then manually joining the results. Same for tracking bridge flows between L2s or scoring wallet quality across chains.
Most teams spend more time wrangling data than actually using it. The crosschain database fixes that.
Flipside's crosschain tables include Solana alongside EVM chains natively. Competitors require separate queries per chain with manual joins for crosschain analysis.
02 / What It Covers
Every table has a blockchain column. Filter by chain, group by chain, or join across chains. Standardized schemas across all 11 networks.
DEX swaps, lending (borrows through liquidations), bridge transfers, LP actions, stablecoins, TVL, and prediction markets. 14 tables.
Bridge deposits, withdrawals, and transfers across 10 chains. Daily metrics break down volume, CEX flows, and stablecoin transfers by chain.
4 tables per chain: address metrics, verified token lists, daily KPIs, and protocol-level activity. 44 tables across all 11 chains.
Hourly prices from CoinGecko and CoinMarketCap, deduplicated into one clean feed. OHLC data, asset metadata, and daily market cap and volume.
13 tables of daily metrics already computed: DEX volume, bridge flows, CEX flows, stablecoins, and TVL. Broken down by chain, protocol, and token.
700M+ labeled addresses, contract metadata, ENS domains, and decoded event logs. See "Coinbase" or "Aave V3" instead of raw hex.
03 / What Sets This Apart
Tables come with USD values already computed, tokens already identified, addresses already labeled, and bot activity already flagged. Your team starts with answers, not data cleanup.
Solana, NEAR, and Sui sit alongside EVM chains with the same column names. Comparing Solana DEX volume to Ethereum DEX volume is a WHERE blockchain IN (...) filter, not a multi-database exercise.
ez_dex_swaps covers every DEX across every chain. ez_lending_borrows covers every lending protocol. When new protocols launch, they appear in the same tables. Your queries don't break.
Every chain stats table splits metrics between all users and quality users (Flipside score ≥ 4). The scoring uses crosschain behavioral signals: CEX deposit patterns, funding source analysis, transaction clustering. Applied consistently across all 11 chains.
When a growth team asks "how many real users does our protocol have?", the answer is already in the data.
The same SQL dialect your BI tools, Python libraries, and AI coding assistants already know. No proprietary query language.
This matters more than it sounds: LLMs like Claude write better queries against standard SQL than proprietary dialects. If you're using AI-assisted analysis, Snowflake SQL gets you better results.
3,000+ automated quality tests run hourly across the full pipeline. If a table has bad data, we catch it before you query it.
04 / Coverage
4 per chain × 11 chains
Swaps, lending, bridges, LP, TVL
Daily metrics by chain & protocol
Blocks, txs, events, traces, transfers
Labels, contracts, tags, ABIs
Hourly prices, OHLC, fundamentals
ERC-20 + native daily snapshots
Domain registrations
Organized across 8 thematic schemas
05 / Use Cases
Compare your chain's DEX volume, TVL, and user growth against competitors. Daily, weekly, or monthly. One query covers every chain.
See where liquidity is moving. Bridge activity, CEX flows, and stablecoin movements tell you which ecosystems are gaining capital before the market catches on.
Build wallet lists filtered to real users across specific chains, protocols, or DeFi activities. Quality scoring removes bots and sybil wallets before you start.
Track lending liquidations, TVL changes, and user retention across every chain your protocol is deployed on. One query, not eleven.
Automate weekly crosschain performance reports for stakeholders. Same schema means numbers are comparable across chains without manual normalization.
Track large liquidity provider movements across chains and protocols. 700M+ labeled addresses mean you see "Jump Trading" instead of a hex string.
06 / Intelligence Agent
The crosschain agent knows every table in the schema. Ask about DEX volume, bridge flows, wallet activity, or protocol performance. It writes the SQL, runs it against Snowflake, and gives you the answer with context.
Crosschain comparisons
"Compare DEX volume on Base vs Arbitrum this week. Who's growing faster?"
Bridge flow analysis
"Where is capital flowing? Show me the top bridge routes this week."
Quality-filtered metrics
"How many real users does Uniswap have on each chain? Filter out bots."
Protocol-level intelligence
"Show me Aave lending liquidations across all chains in the last 30 days."
07 / Automate Intelligence
Set up automations that query crosschain metrics on a schedule, run the results through an AI agent for analysis, and deliver briefings to Slack, email, or dashboards.
Automations run on your schedule and deliver crosschain insights to Slack, email, or dashboards.
Daily chain comparisons
Wake up to a summary of DEX volume, TVL shifts, and user growth across every chain. Delivered before your first meeting.
Bridge flow alerts
Know when bridge volume spikes on a specific route or when capital starts flowing to a chain you're watching.
Ecosystem reporting
Auto-generate weekly performance reports that compare chains with the same metrics and definitions every time.
08 / FAQ
Ethereum, Solana, Polygon, Arbitrum, Optimism, Base, BSC, Avalanche, NEAR, Sui, and Ink. All 11 chains use the same table structure and column names, so a query that works on Ethereum also works on Solana with a single filter change.
Each blockchain has its own schema, data model, and naming conventions. Normally you'd need to write separate queries per chain and manually join the results. Flipside's crosschain database normalizes all chains into standardized schemas. Comparing Base DEX volume to Arbitrum DEX volume is a WHERE blockchain IN ('base', 'arbitrum') filter on a single table.
Standard Snowflake SQL. No proprietary query language to learn. Any BI tool, Python library, or AI assistant that speaks SQL can query the data directly.
Flipside assigns each address a score (0-15) based on crosschain behavioral signals: CEX deposit patterns, funding sources, and transaction clustering. A score of 4 or higher indicates a real user. Every chain stats table includes both total and quality-filtered metrics, so you can separate genuine activity from bot traffic without extra work.
Most tables update within hours of onchain confirmation. Hourly core metrics update in near real-time. Historical coverage goes back to each chain's genesis block. 3,000+ automated quality tests run hourly to catch issues before they reach your queries.
Yes. The crosschain database sits in the same Snowflake environment as Flipside's per-chain databases (e.g., ethereum.core, solana.defi). You can join between them freely.
95+ tables organized across 8 schemas: Chain Stats (44), DeFi (14), Aggregate Stats (13), EVM (10), Core Dimensions (6), Pricing (5), Balances (2), and ENS (1). The DeFi schema alone covers DEX swaps, the full lending lifecycle, bridge activity, LP actions, stablecoins, TVL, and prediction markets.
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11 blockchains, 95+ tables, standard Snowflake SQL. DeFi, bridges, pricing, and chain stats in standardized schemas.