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Schema: crosschain.balances Table: ez_optimism_balances_erc20_daily Type: View

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What

This convenience table provides a comprehensive view of daily ERC20 token balance snapshots with enriched metadata including decimal adjustments, USD values, and token information, specifically covering verified tokens only. It simplifies balance analysis by capturing end-of-day token holdings for each address-token pair through direct balanceOf contract calls across all supported EVM blockchains. It contains a column for the blockchain the balance snapshot occurred on, which is an important filter and join key. See evm.dim_chains for a list of all supported EVM chains. Note: This is a unified view that combines ERC20 token balance data from multiple EVM blockchains. Each row includes a blockchain identifier to distinguish between different networks.

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Key Use Cases

  • Daily portfolio tracking and balance monitoring for ERC20 tokens
  • Historical balance analysis and trend identification
  • Token holder distribution analysis at daily granularity
  • Wallet balance snapshots for reporting and analytics
  • Cross-token balance comparisons and concentration analysis
  • Token supply distribution monitoring over time
  • Daily balance-based yield and return calculations

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Important Relationships

  • Join with evm__fact_blocks: Use block_number and blockchain for block metadata and timestamps
  • Join with core__dim_labels: Use address and blockchain for entity identification and categorization
  • Join with evm__dim_contracts: Use contract_address and blockchain for token contract details
  • Complement to balances__ez_balances_native_daily: Complete picture of token holdings
  • Join with evm__ez_token_transfers: Compare daily balances with transfer activity

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Commonly-used Fields

  • address: The account address holding the token balance
  • contract_address: The ERC20 token contract address
  • symbol: Token symbol (USDC, WETH, etc.)
  • balance: Token balance at end of day, decimal adjusted to standard units
  • balance_usd: USD value of the token balance at end of day
  • balance_raw: Raw balance in smallest token unit (wei equivalent)
  • balance_precise: Precise decimal-adjusted balance as string
  • decimals: Number of decimal places for the token
  • block_date: The date for which this balance snapshot was taken
  • blockchain: The blockchain the balance snapshot occurred on

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Sample queries

Daily Token Holdings by Address 
SELECT 
    block_date,
    address,
    symbol,
    balance,
    balance_usd,
    contract_address,
    blockchain
FROM crosschain.balances.ez_balances_erc20_daily
WHERE address = LOWER('0x1234567890123456789012345678901234567890')
    AND block_date >= CURRENT_DATE - 30
    AND balance > 0
    AND blockchain = 'ethereum'
ORDER BY block_date DESC, balance_usd DESC;
Token Holder Count Trends 
SELECT 
    block_date,
    symbol,
    contract_address,
    blockchain,
    COUNT(DISTINCT address) AS holder_count,
    SUM(balance) AS total_supply_tracked,
    AVG(balance) AS avg_balance,
    MEDIAN(balance) AS median_balance
FROM crosschain.balances.ez_balances_erc20_daily
WHERE block_date >= CURRENT_DATE - 90
    AND balance > 0
    AND symbol IS NOT NULL
    AND blockchain = 'ethereum'
GROUP BY 1, 2, 3, 4
ORDER BY 1 DESC, holder_count DESC;
Portfolio Value Evolution 
-- Track portfolio value changes over time for specific addresses
SELECT 
    block_date,
    address,
    blockchain,
    COUNT(DISTINCT contract_address) AS token_count,
    SUM(balance_usd) AS total_portfolio_usd,
    STRING_AGG(
        CASE WHEN balance_usd > 100 
        THEN symbol || ': $' || ROUND(balance_usd, 2) 
        END, ', '
    ) AS major_holdings
FROM crosschain.balances.ez_balances_erc20_daily
WHERE address IN (
    SELECT DISTINCT address 
    FROM crosschain.balances.ez_balances_erc20_daily 
    WHERE balance_usd > 10000
        AND blockchain = 'ethereum'
    LIMIT 100
)
    AND block_date >= CURRENT_DATE - 30
    AND balance > 0
    AND blockchain = 'ethereum'
GROUP BY 1, 2, 3
HAVING total_portfolio_usd > 1000
ORDER BY 1 DESC, total_portfolio_usd DESC;
Token Distribution Analysis 
-- Analyze token concentration and distribution patterns
SELECT 
    symbol,
    contract_address,
    block_date,
    blockchain,
    COUNT(DISTINCT address) AS total_holders,
    COUNT(DISTINCT CASE WHEN balance >= 1000 THEN address END) AS holders_1k_plus,
    COUNT(DISTINCT CASE WHEN balance >= 10000 THEN address END) AS holders_10k_plus,
    MAX(balance) AS max_balance,
    PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY balance) AS p95_balance,
    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY balance) AS median_balance
FROM crosschain.balances.ez_balances_erc20_daily
WHERE block_date = CURRENT_DATE - 1
    AND balance > 0
    AND symbol IS NOT NULL
    AND blockchain = 'ethereum'
GROUP BY 1, 2, 3, 4
HAVING total_holders >= 100
ORDER BY total_holders DESC
LIMIT 50;
Daily Balance Changes 
-- Compare daily balances to identify significant changes
WITH daily_changes AS (
    SELECT 
        address,
        contract_address,
        symbol,
        block_date,
        blockchain,
        balance,
        balance_usd,
        LAG(balance) OVER (
            PARTITION BY address, contract_address, blockchain 
            ORDER BY block_date
        ) AS prev_balance,
        LAG(balance_usd) OVER (
            PARTITION BY address, contract_address, blockchain 
            ORDER BY block_date
        ) AS prev_balance_usd
    FROM crosschain.balances.ez_balances_erc20_daily
    WHERE block_date >= CURRENT_DATE - 7
        AND balance > 0
        AND blockchain = 'ethereum'
)
SELECT 
    block_date,
    address,
    symbol,
    blockchain,
    balance,
    prev_balance,
    balance - prev_balance AS balance_change,
    balance_usd - prev_balance_usd AS balance_change_usd,
    CASE 
        WHEN prev_balance > 0 
        THEN ((balance - prev_balance) / prev_balance) * 100 
        ELSE NULL 
    END AS pct_change
FROM daily_changes
WHERE ABS(balance_change_usd) > 1000
    AND prev_balance IS NOT NULL
ORDER BY ABS(balance_change_usd) DESC
LIMIT 100;

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Columns

Column NameData TypeDescription
BLOCKCHAINTEXTThe blockchain the record occurred on. See evm.dim_chains for a list of all EVM chains. Format: VARCHAR Example: ‘ethereum’ Usage: Filtering by blockchain Joining across tables Analyzing chain-specific patterns
BLOCK_NUMBERNUMBERSequential counter representing the position of a block in the blockchain since genesis (block 0). Key Facts: Immutable once finalized Primary ordering mechanism for blockchain data Increments by 1 for each new block Used as a proxy for time in many analyses Usage in Queries: Important: Block numbers are chain-specific. Block 15000000 on Ethereum ≠ block 15000000 on Polygon.
BLOCK_DATEDATEThe date for which this balance snapshot represents the end-of-day token balance. Example: ‘2025-07-04’
ADDRESSTEXTThe account address whose token balance is recorded in this daily snapshot. Example: ‘0x1234567890123456789012345678901234567890’
CONTRACT_ADDRESSTEXTThe verified ERC20 token contract address for which the balance is recorded. Example: ‘0xa0b86a33e6eb88b4d81b15e4e60c8a5b776e3b7a’
DECIMALSNUMBERNumber of decimal places for the token, used for proper decimal adjustment in balance calculations. Example: 6
SYMBOLTEXTThe token symbol for the ERC20 token. Example: ‘USDC’
BALANCE_HEXTEXTHexadecimal representation of the token balance as returned by the balanceOf contract call. Example: ‘0x0000000000000000000000000000000000000000000000000000000000364d3e’
BALANCE_RAWNUMBERToken balance in the smallest unit (wei equivalent) without decimal adjustment, as returned by the contract. Example: 1000000000
BALANCE_PRECISETEXTToken balance with proper decimal adjustment, returned as a string to preserve precision. Example: ‘1000.000000’
BALANCEFLOATToken balance with decimal adjustment converted to a float for easier mathematical operations. Example: 1000.0
BALANCE_USDFLOATUSD value of the token balance at the end of the day, calculated using hourly price data. Example: 1000.50
EZ_BALANCES_ERC20_DAILY_IDTEXTPrimary key - unique identifier for each row ensuring data integrity. Format: Usually VARCHAR containing composite key generated using MD5 hash of the relevant columns. Example: MD5(blocknumber, txhash, trace_index) Usage: Deduplication in incremental loads Join operations for data quality checks Troubleshooting specific records Important: Implementation varies by table - check table-specific documentation.
INSERTED_TIMESTAMPTIMESTAMP_NTZUTC timestamp when the record was first added to the Flipside database. Format: TIMESTAMP_NTZ Use Cases: Data freshness monitoring Incremental processing markers Debugging data pipeline issues SLA tracking Query Example:
MODIFIED_TIMESTAMPTIMESTAMP_NTZUTC timestamp of the most recent update to this record. Format: TIMESTAMP_NTZ Triggers for Updates: Data corrections Enrichment additions Reprocessing for accuracy Schema migrations Monitoring Usage: