Minute Prices

Real-time minute-by-minute price data for tokens across all supported blockchains

prices.minute

Overview

The prices.minute table provides the most granular price data for tokens across multiple blockchains, with minute-level precision. This is the highest resolution price data available in the Dune platform.

Table Schema

Column	Type	Description
blockchain	varchar	Blockchain identifier (e.g., ‘ethereum’, ‘arbitrum’)
contract_address	varbinary	Token contract address (fixed address for native tokens)
symbol	varchar	Token symbol (e.g., ‘ETH’, ‘USDC’)
timestamp	timestamp	Minute timestamp
price	double	Token price in USD (volume-weighted average)
decimals	int	Token decimals
volume	double	Trading volume in USD (from price source)
source	varchar	Data source (‘coinpaprika’ or ‘dex.trades’)

Implementation Details

The minute prices are built using a sparse hour interpolation approach:

1. Source from hourly data: Uses prices.hour as the source instead of raw minute-level data
2. Linear interpolation: Implements linear interpolation between hourly anchor points to create smooth minute-level data
3. Noise reduction: Reduces noise and outliers by using stable hourly data points as anchors
4. Forward-filling: The system forward-fills with the last available price for a maximum of 48 hours (2880 minutes) to avoid stale data
5. Continuous time series: Provides minute-by-minute data points for every minute between hourly anchors

This approach ensures more reliable and consistent minute-level pricing while maintaining the granularity needed for high-frequency analysis.

Usage

This table is ideal for high-frequency analysis and examining short-term price movements. It’s particularly useful for studying price impacts of specific events or transactions with high temporal precision.

Note: The minute-level data is interpolated from hourly anchor points, providing smooth and consistent pricing while reducing the impact of noise and outliers that can occur in raw minute-level data.

Latency and Update Frequency

The prices.minute table is updated hourly based on the upstream data pipeline. As a result, prices typically have a latency of approximately 1 hour from real-time.

Usage Examples

Here are some examples of how to use the prices tables.

Get minute-by-minute ETH prices during a specific event:

SELECT
  timestamp,
  price
FROM prices.minute
WHERE
  blockchain = 'ethereum'
  AND contract_address = 0xc02aaa39b223fe8d0a0e5c4f27ead9083c756cc2 -- WETH
  AND timestamp >= NOW() - INTERVAL '2' HOUR
  AND timestamp <= NOW() - INTERVAL '1' HOUR
ORDER BY timestamp

Analyze price volatility within short time frames:

SELECT
  date_trunc('hour', timestamp) as hour,
  max(price) - min(price) as price_range,
  (max(price) - min(price)) / min(price) * 100 as volatility_pct
FROM prices.minute
WHERE
  blockchain = 'ethereum'
  AND contract_address = 0xc02aaa39b223fe8d0a0e5c4f27ead9083c756cc2 -- WETH
  AND timestamp >= NOW() - INTERVAL '1' DAY
GROUP BY 1
ORDER BY 1

Data Quality Notes

• Due to its high granularity, queries on this table may be more resource-intensive
• Consider using prices.hour or prices.day for longer time ranges if minute-level precision is not required
• Native tokens (like ETH, BNB) are assigned fixed addresses for consistency
• Always use contract_address and blockchain for precise token identification, never use symbol for joins or filters
• Interpolated Pricing: Minute-level data is interpolated from hourly anchor points, providing smoother and more consistent pricing
• Reduced Noise: The interpolation approach reduces the impact of noise and outliers that can occur in raw minute-level data
• 48-Hour Forward-Fill: The system forward-fills with the last available price for a maximum of 48 hours (2880 minutes) to avoid stale data
• Data Limitations: While the interpolation approach improves data quality, users should always validate prices for critical applications