Available Tables
Apex data is available in two main tables:- ez_metrics: Main aggregated metrics for the Apex Protocol across all supported chains
- ez_metrics_by_chain: Chain-specific perpetual trading metrics broken down by individual blockchain
Table Schema
Perpetual Trading Metrics
| Table Name | Column Name | Description |
|---|---|---|
| ez_metrics | perp_volume | The total trading volume on the perpetuals exchange |
| ez_metrics | trading_volume | Same as perp_volume (legacy naming) |
| ez_metrics | app | Always ‘apex’ for consistency |
| ez_metrics | category | Always ‘DeFi’ for consistency |
Chain-Specific Trading Metrics
| Table Name | Column Name | Description |
|---|---|---|
| ez_metrics_by_chain | perp_volume | Perpetual trading volume on the specific chain |
| ez_metrics_by_chain | trading_volume | Same as perp_volume (legacy naming) |
| ez_metrics_by_chain | chain | The blockchain identifier |
| ez_metrics_by_chain | app | Always ‘apex’ for consistency |
| ez_metrics_by_chain | category | Always ‘DeFi’ for consistency |
Market and Token Metrics
| Table Name | Column Name | Description |
|---|---|---|
| ez_metrics | price | The price of APEX token in USD |
| ez_metrics | market_cap | The market cap of APEX token in USD |
| ez_metrics | fdmc | The fully diluted market cap of APEX token in USD |
| ez_metrics | token_volume | The trading volume of APEX token in USD |
| ez_metrics | token_turnover_circulating | The turnover of APEX token based on circulating supply |
| ez_metrics | token_turnover_fdv | The turnover of APEX token based on fully diluted supply |
Sample Queries
Basic Perpetual Trading Activity Query
-- Pull fundamental perpetual trading data for Apex
SELECT
date,
perp_volume,
price,
market_cap,
token_volume,
perp_volume / NULLIF(token_volume, 0) as perp_to_token_volume_ratio
FROM
art_share.apex.ez_metrics
WHERE
date >= DATEADD(month, -3, CURRENT_DATE())
ORDER BY
date ASC
Cross-Chain Trading Analysis
-- Analyze perpetual trading activity across different chains
SELECT
date,
chain,
perp_volume,
LAG(perp_volume, 1) OVER (PARTITION BY chain ORDER BY date) as prev_day_volume,
LAG(perp_volume, 7) OVER (PARTITION BY chain ORDER BY date) as volume_7d_ago,
(perp_volume - LAG(perp_volume, 1) OVER (PARTITION BY chain ORDER BY date)) / NULLIF(LAG(perp_volume, 1) OVER (PARTITION BY chain ORDER BY date), 0) * 100 as volume_change_1d,
(perp_volume - LAG(perp_volume, 7) OVER (PARTITION BY chain ORDER BY date)) / NULLIF(LAG(perp_volume, 7) OVER (PARTITION BY chain ORDER BY date), 0) * 100 as volume_growth_7d
FROM
art_share.apex.ez_metrics_by_chain
WHERE
date >= DATEADD(month, -2, CURRENT_DATE())
ORDER BY
chain, date ASC
Chain Volume Comparison
-- Compare perpetual trading volumes across different chains
SELECT
chain,
SUM(perp_volume) as total_volume,
AVG(perp_volume) as avg_daily_volume,
MAX(perp_volume) as peak_daily_volume,
MIN(perp_volume) as min_daily_volume,
COUNT(CASE WHEN perp_volume > 0 THEN 1 END) as active_days,
STDDEV(perp_volume) as volume_volatility,
STDDEV(perp_volume) / NULLIF(AVG(perp_volume), 0) as coefficient_of_variation
FROM
art_share.apex.ez_metrics_by_chain
WHERE
date >= DATEADD(month, -3, CURRENT_DATE())
GROUP BY
chain
ORDER BY
total_volume DESC
Market Performance vs Trading Activity
-- Analyze APEX token market performance vs perpetual trading activity
SELECT
date,
perp_volume,
price,
market_cap,
token_volume,
token_turnover_circulating,
token_turnover_fdv,
token_volume / NULLIF(perp_volume, 0) * 100 as token_vs_perp_volume_ratio,
market_cap / NULLIF(perp_volume, 0) as mcap_to_trading_volume_ratio,
token_turnover_circulating * 100 as daily_token_turnover_percentage,
token_turnover_fdv * 100 as daily_fdv_turnover_percentage
FROM
art_share.apex.ez_metrics
WHERE
date >= DATEADD(month, -3, CURRENT_DATE())
ORDER BY
date ASC
Trading Volume Trends and Growth
-- Track Apex perpetual trading volume trends and growth patterns
SELECT
date,
perp_volume,
-- Moving averages
AVG(perp_volume) OVER (ORDER BY date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) as avg_volume_7d,
AVG(perp_volume) OVER (ORDER BY date ROWS BETWEEN 29 PRECEDING AND CURRENT ROW) as avg_volume_30d,
AVG(perp_volume) OVER (ORDER BY date ROWS BETWEEN 89 PRECEDING AND CURRENT ROW) as avg_volume_90d,
-- Growth rates
LAG(perp_volume, 7) OVER (ORDER BY date) as volume_7d_ago,
LAG(perp_volume, 30) OVER (ORDER BY date) as volume_30d_ago,
(perp_volume - LAG(perp_volume, 7) OVER (ORDER BY date)) / NULLIF(LAG(perp_volume, 7) OVER (ORDER BY date), 0) * 100 as volume_growth_7d,
(perp_volume - LAG(perp_volume, 30) OVER (ORDER BY date)) / NULLIF(LAG(perp_volume, 30) OVER (ORDER BY date), 0) * 100 as volume_growth_30d,
-- Trend analysis
perp_volume / NULLIF(AVG(perp_volume) OVER (ORDER BY date ROWS BETWEEN 29 PRECEDING AND CURRENT ROW), 0) as volume_vs_30d_avg_ratio
FROM
art_share.apex.ez_metrics
WHERE
date >= DATEADD(month, -6, CURRENT_DATE())
ORDER BY
date ASC
Chain Dominance and Market Share
-- Analyze which chains dominate Apex's perpetual trading volume
WITH daily_totals AS (
SELECT
date,
SUM(perp_volume) as total_daily_volume
FROM
art_share.apex.ez_metrics_by_chain
WHERE
date >= DATEADD(month, -2, CURRENT_DATE())
GROUP BY
date
),
chain_shares AS (
SELECT
ebc.date,
ebc.chain,
ebc.perp_volume,
dt.total_daily_volume,
ebc.perp_volume / NULLIF(dt.total_daily_volume, 0) * 100 as daily_share_percentage
FROM
art_share.apex.ez_metrics_by_chain ebc
JOIN
daily_totals dt ON ebc.date = dt.date
WHERE
ebc.date >= DATEADD(month, -2, CURRENT_DATE())
)
SELECT
chain,
AVG(daily_share_percentage) as avg_share_percentage,
MAX(daily_share_percentage) as peak_share_percentage,
MIN(daily_share_percentage) as min_share_percentage,
SUM(perp_volume) as total_volume,
COUNT(*) as active_days,
STDDEV(daily_share_percentage) as share_volatility
FROM
chain_shares
WHERE
perp_volume > 0
GROUP BY
chain
ORDER BY
avg_share_percentage DESC
Token Market Analysis
-- Analyze APEX token market metrics and trading patterns
SELECT
date,
price,
market_cap,
fdmc,
token_volume,
token_turnover_circulating,
token_turnover_fdv,
perp_volume,
-- Token valuation metrics
market_cap / NULLIF(fdmc, 0) * 100 as circulating_percentage,
token_volume / NULLIF(market_cap, 0) * 100 as daily_volume_to_mcap_ratio,
-- Protocol activity correlation
perp_volume / NULLIF(token_volume, 0) as perp_to_token_volume_ratio,
market_cap / NULLIF(perp_volume, 0) as mcap_per_dollar_traded
FROM
art_share.apex.ez_metrics
WHERE
date >= DATEADD(month, -2, CURRENT_DATE())
AND price > 0
ORDER BY
date ASC
High Volume Trading Analysis
-- Identify and analyze high volume trading periods
WITH volume_stats AS (
SELECT
AVG(perp_volume) as avg_volume,
STDDEV(perp_volume) as stddev_volume,
PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY perp_volume) as volume_95th_percentile
FROM
art_share.apex.ez_metrics
WHERE
date >= DATEADD(month, -3, CURRENT_DATE())
AND perp_volume > 0
)
SELECT
date,
perp_volume,
price,
token_volume,
vs.avg_volume,
vs.volume_95th_percentile,
(perp_volume - vs.avg_volume) / NULLIF(vs.stddev_volume, 0) as volume_z_score,
perp_volume / NULLIF(vs.avg_volume, 0) as volume_multiple,
CASE
WHEN perp_volume > vs.volume_95th_percentile THEN 'Top 5%'
WHEN perp_volume > vs.avg_volume + 2 * vs.stddev_volume THEN 'Very High'
WHEN perp_volume > vs.avg_volume + vs.stddev_volume THEN 'High'
WHEN perp_volume < vs.avg_volume - vs.stddev_volume THEN 'Low'
ELSE 'Normal'
END as volume_category
FROM
art_share.apex.ez_metrics
CROSS JOIN
volume_stats vs
WHERE
date >= DATEADD(month, -3, CURRENT_DATE())
AND perp_volume > vs.avg_volume + vs.stddev_volume
ORDER BY
perp_volume DESC
Weekly Performance Summary
-- Weekly aggregated performance summary for Apex
SELECT
DATE_TRUNC('week', date) as week,
SUM(perp_volume) as total_weekly_volume,
AVG(perp_volume) as avg_daily_volume,
MAX(perp_volume) as peak_daily_volume,
MIN(perp_volume) as min_daily_volume,
AVG(price) as avg_token_price,
SUM(token_volume) as total_token_volume,
AVG(market_cap) as avg_market_cap,
AVG(token_turnover_circulating) * 7 as estimated_weekly_turnover
FROM
art_share.apex.ez_metrics
WHERE
date >= DATEADD(month, -3, CURRENT_DATE())
GROUP BY
DATE_TRUNC('week', date)
ORDER BY
week DESC
Multi-Chain Performance Comparison
-- Compare performance and growth across different chains
WITH chain_metrics AS (
SELECT
chain,
date,
perp_volume,
LAG(perp_volume, 7) OVER (PARTITION BY chain ORDER BY date) as volume_7d_ago,
LAG(perp_volume, 30) OVER (PARTITION BY chain ORDER BY date) as volume_30d_ago,
ROW_NUMBER() OVER (PARTITION BY chain ORDER BY perp_volume DESC) as volume_rank
FROM
art_share.apex.ez_metrics_by_chain
WHERE
date >= DATEADD(month, -2, CURRENT_DATE())
)
SELECT
date,
chain,
perp_volume,
volume_7d_ago,
volume_30d_ago,
volume_rank,
(perp_volume - volume_7d_ago) / NULLIF(volume_7d_ago, 0) * 100 as growth_7d,
(perp_volume - volume_30d_ago) / NULLIF(volume_30d_ago, 0) * 100 as growth_30d,
CASE
WHEN volume_rank = 1 THEN 'Peak Performance'
WHEN volume_rank <= 5 THEN 'High Performance'
ELSE 'Standard Performance'
END as performance_tier
FROM
chain_metrics
WHERE
date >= DATEADD(month, -1, CURRENT_DATE())
AND volume_7d_ago IS NOT NULL
ORDER BY
date DESC, perp_volume DESC