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Blockchains (L2)

Unichain

# Unichain Transaction count Methodology

## 1. Overview

The Unichain transaction count metric measures the daily number of unique transactions processed on the Unichain blockchain, aggregated by recipient address. This metric provides insights into network activity and usage patterns by tracking transaction volume to different destination addresses. The calculation uses an approximate distinct count method to efficiently process large volumes of transaction data and groups results by day and recipient address.

## 2. Data sources

- **Blockchain transaction records**: Raw Unichain blockchain transaction data containing transaction hashes, timestamps, sender and recipient addresses, and gas usage information
- **Chain availability configuration**: Token Terminal's internal system that defines valid data availability windows for quality assurance
- **Table modification tracking**: Internal system that tracks when metric tables were last updated to support incremental processing

## 3. Step-by-step calculation

### Component A: Raw transaction extraction
- **Purpose**: Extract and standardize raw transaction data from the Unichain blockchain
- **Logic**: Retrieve all transaction records from Unichain blockchain data, including block timestamps, transaction hashes, sender addresses (`from_address`), recipient addresses (`to_address`), and gas usage metrics. Cast all fields to appropriate data types for consistency - timestamps as timestamp type, addresses as strings, and gas-related fields as high-precision numeric types. Hardcode token information to identify ETH as the native token with address `0x4200000000000000000000000000000000000006`.
- **Key fields**: `block_timestamp` for timing, `transaction_hash` for uniqueness, `from_address` and `to_address` for transaction flow, `gas_used` and related gas fields for cost analysis

### Component B: Daily transaction aggregation
- **Purpose**: Aggregate unique transactions by day and recipient address
- **Logic**: Truncate block timestamps to daily boundaries to create consistent time buckets. Group transactions by the truncated timestamp, recipient address, and standard metadata fields including chain identifier, market sector, and business segment. Count distinct transaction hashes using an approximate counting method for performance optimization on large datasets. This creates a daily count of unique transactions received by each address.
- **Key fields**: `timestamp` (truncated to day), `to_address` for grouping, `transaction_count` as the approximate distinct count of `transaction_hash`

### Final aggregation
- **Combining components**: The daily aggregated transaction counts flow directly into the finalization process without additional combining steps
- **Schema standardization**: Apply the `finalize_metric_transaction_count` macro to ensure consistent schema structure, validate all identifier fields, and implement a zero-fill strategy for any missing days or addresses to maintain complete time series
- **Quality filtering**: Apply chain availability filters to exclude data from periods when Unichain data might be incomplete or unreliable
- **Incremental processing**: For efficiency, only process transactions from recent days based on the last modification timestamp, with a configurable lookback period to handle late-arriving data
- **Final calculation**: The final metric represents the daily count of unique transactions sent to each recipient address on Unichain, with metadata identifying it as a blockchain Layer 2 metric in the blockchains market sector

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

Confirmed transactions added to the blockchain.

UnichainUNI

Transaction count

Transaction count

Competitive landscape

Chain breakdown