Fraxtal batches users' transactions and submits them to Ethereum, paying a share of the transaction fees to Ethereum validators (expense).

Fraxtal is an Ethereum Layer 2 (L2) blockchain built on the OP Stack by Frax Finance. It uses frxETH as the gas token and features a blockspace incentive system called Flox. Fraxtal launched in February 2024.

Frax Finance team owns and governs the protocol. Frax Finance's investors include Dragonfly Capital, Mechanism Capital, Galaxy Digital, etc.

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Blockchains (L2)

Fraxtal

# Fraxtal Active addresses (daily) Methodology

## 1. Overview

The Fraxtal Active Addresses Daily metric measures the number of unique addresses that initiated at least one transaction on the Fraxtal blockchain each day. This metric provides insights into daily user activity and adoption on the Fraxtal Layer 2 network. For blockchain metrics, active addresses are equivalent to active users, as each unique sender address represents a distinct user interacting with the network.

## 2. Data sources

- **Fraxtal transaction records**: Raw transaction data from the Fraxtal L2 blockchain containing transaction timestamps, hashes, and sender addresses
- **Chain availability configuration**: Data quality filters to ensure complete and reliable blockchain data coverage

## 3. Step-by-step calculation

### Component A: User fact extraction
- **Purpose**: Extract and standardize user interaction data from raw Fraxtal transactions
- **Logic**: Process raw Fraxtal transaction records to identify unique users and their activity. Extract the `block_timestamp`, `transaction_hash`, and `from_address` fields from each transaction. Classify all sender addresses as "Transaction sender" user type and categorize under the "blockchains_l2" market sector and "blockchain" business segment. Set `product_id` to null since this is measured at the blockchain level rather than specific product level.
- **Key fields**: `block_timestamp` for timing, `from_address` as the unique user identifier, `transaction_hash` for transaction tracking, and metadata fields for proper categorization

### Component B: Daily user aggregation  
- **Purpose**: Calculate distinct active users per day using efficient counting methods
- **Logic**: Group transactions by day using timestamp truncation to day boundaries. For each day, identify all distinct user addresses that sent transactions. Apply HyperLogLog counting with 15 bits of precision to enable scalable distinct user counting while supporting incremental processing. This creates the base dataset of daily active users with proper temporal boundaries.
- **Key fields**: `timestamp` truncated to day level, `user_address` for distinct counting, HLL sketch data for efficient aggregation

### Component C: Dimensional breakdowns
- **Purpose**: Create multiple dimensional views of the daily active user data
- **Logic**: Generate separate aggregations for different analytical perspectives by merging HLL sketches and extracting final counts:
  - **Project level**: Aggregate all users across the entire Fraxtal ecosystem with `dimensions` set to "project_dbt_tag"
  - **Chain level**: Break down users by specific blockchain with `dimensions` set to "chain" and `chain_id` set to "fraxtal"  
  - **User type level**: Segment users by interaction type with `dimensions` set to "user_type"
  - **Product level**: Categorize by product (null for blockchain-level metrics) with `dimensions` set to "product_id"
- **Key fields**: `dimensions` to specify breakdown type, `chain_id`, `user_type`, `product_id` for segmentation, `user_dau` containing the distinct user count

### Final aggregation
- **Combining components**: Union all dimensional breakdown results to create a comprehensive dataset with multiple analytical perspectives in a single table
- **Schema standardization**: Apply the `finalize_metric_user_dau` macro to standardize field names, data types, and handle missing days by filling with zero values to ensure complete time series
- **Data quality filtering**: Apply chain availability filters to exclude periods with incomplete or unreliable data coverage
- **Field transformation**: Rename the `user_dau` field to `active_addresses_daily` to reflect that for blockchain metrics, active users are measured as active addresses
- **Final calculation**: The result is the count of distinct addresses that initiated transactions on Fraxtal each day, with zero values for days with no activity or data gaps, broken down by multiple dimensions for comprehensive analysis

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

Unique active addresses over a fixed 24-hour window.

FraxtalFXTL

Active addresses (daily)

Active addresses (daily)

Competitive landscape

Chain breakdown