Validators process transactions and receive validator rewards (supply-side fees).

AVAX is a smart contract platform for decentralized applications (a blockchain). Avalanche was founded by Emin Gün Sirer and launched in 2019.

AVAX holders own and govern the protocol. They currently take (burn) all of the total transaction fees paid by users (revenue). AVAXs investors include a16z, Polychain, Galaxy Digital, etc.

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Blockchains (L1)

Avalanche

# Avalanche Transaction count Methodology

## 1. Overview

The Avalanche transaction count metric measures the daily number of unique transactions on the Avalanche blockchain. This metric provides insight into network activity and adoption by counting distinct transactions per day, segmented by the destination contract address. The calculation uses approximate distinct counting for efficiency and enriches results with contract labels for better categorization.

## 2. Data sources

- **Avalanche transaction records**: Raw transaction data from the Avalanche blockchain containing transaction hashes, sender and receiver addresses, gas usage information, block timestamps, and block numbers
- **Account label database**: Third-party database providing human-readable names and classifications for Avalanche contract addresses and accounts

## 3. Step-by-step calculation

### Component A: Transaction data extraction
- **Purpose**: Extract and standardize all Avalanche transaction data with gas information
- **Logic**: Raw Avalanche transaction records are processed to extract essential fields including `block_timestamp`, `transaction_hash`, `from_address`, `to_address`, and gas-related fields. Gas prices are converted from wei to AVAX units by dividing the `receipt_effective_gas_price` by 10^18. The model includes a hardcoded WAVAX token address constant for reference. Data is filtered incrementally based on block timestamp to process only new or recently modified records.
- **Key fields**: `transaction_hash` (unique transaction identifier), `to_address` (destination contract or account), `block_timestamp` (transaction execution time), `gas_used` and `effective_gas_price` (transaction cost data)

### Component B: Daily transaction aggregation
- **Purpose**: Count unique transactions per day grouped by destination address
- **Logic**: Transaction data is aggregated by truncating timestamps to daily boundaries. An approximate distinct count is performed on `transaction_hash` grouped by the truncated timestamp and `to_address`. This creates daily transaction counts for each destination address. Standard metadata fields are added including chain identifier, market sector, and business segment classifications.
- **Key fields**: `timestamp` (daily boundary), `transaction_count` (approximate distinct count of transaction hashes), `to_address` (destination grouping key)

### Component C: Address labeling enrichment
- **Purpose**: Add human-readable names to contract addresses for better categorization
- **Logic**: The daily transaction counts are enriched by left joining with the account labels database using `to_address` as the join key. The labels database is filtered to only include Avalanche chain records and provides `account_title` mappings. Addresses without labels are classified as 'Unlabeled'. This step helps categorize transactions by contract type or known protocol names.
- **Key fields**: `contract_name` (derived from account title or 'Unlabeled'), `account_address` (join key for label matching)

### Final aggregation
- **Combining components**: The enriched transaction data flows through the `finalize_metric_transaction_count` macro which applies standardized schema validation, ensures proper field typing, and implements gap-filling logic
- **Currency conversion**: No currency conversion is performed as this metric counts transactions rather than monetary values
- **Time aggregation**: Daily boundaries are established by truncating block timestamps to day level, creating consistent 24-hour periods for transaction counting
- **Final calculation**: The final metric represents the approximate distinct count of transaction hashes per day, segmented by destination contract with associated labels. A chain availability filter is applied to ensure data quality and completeness before final output.

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

Confirmed transactions added to the blockchain.

AvalancheAVAX

Transaction count

Transaction count

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