Axelar Network node operators validate cross-chain transactions. They currently take a cut of transfer fees (supply-side fees).

Axelar Network is an interoperability protocol that allows for decentralized transfers of data and assets between blockchains. Axelar Network was founded by Sergey Gorbunov and Georgios Vlachos, and was launched in 2022. This dashboard currently only includes data for the following chains: Arbitrum, Avalanche, Base, BNB Chain, Celo, Ethereum, Fantom, Optimism, and Polygon.

AXL tokenholders own and govern the protocol. They currently take a cut of transfer fees paid by transfer senders (revenue). Axelar Network’s investors include Polychain Capital, Dragonfly Capital, North Island Ventures, etc.

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Interoperability

Axelar Network

# Axelar Network Active users (monthly) Methodology

## 1. Overview

Monthly Active Users (MAU) for Axelar measures the number of unique users who interact with the Axelar protocol within any 30-day rolling window. This metric captures user engagement across Axelar's interoperability services, including General Message Passing (GMP) calls and cross-chain token transfers. The calculation uses HyperLogLog algorithms for efficient distinct user counting and provides breakdowns by project level, individual chains, user types, and product IDs.

## 2. Data sources

The calculation relies on several key blockchain data sources:

- **Axelar Gateway smart contract events**: Parsed events from Axelar Gateway contracts deployed across 9 EVM chains (Ethereum, Arbitrum, Base, Optimism, Polygon, BSC, Avalanche, Fantom, Celo) including `Gateway_ContractCallWithToken_event`, `Gateway_ContractCall_event`, `Gateway_Executed_event`, and `Gateway_TokenSent_event`
- **Blockchain transaction records**: Transaction data from all supported chains containing user addresses and transaction metadata
- **Token transfer events**: On-chain token transfer events that validate actual token movements and amounts
- **Token metadata**: Token symbol and identification information for transaction classification
- **Chain mapping data**: Internal mappings between chain identifiers and standardized chain names

## 3. Step-by-step calculation

### Component A: Daily active user extraction
- **Purpose**: Identifies unique daily users across all Axelar protocol interactions
- **Logic**: Extracts user addresses from three types of Axelar interactions: GMP messaging transactions (using `Gateway_ContractCallWithToken_event` and `Gateway_ContractCall_event`), completed transfers on destination chains (using `Gateway_Executed_event`), and initiated transfers on source chains (using `Gateway_TokenSent_event`). Each interaction type joins Gateway contract events with blockchain transaction records to extract the `from_address` as the user identifier. For transactions involving tokens, the system validates that token transfer amounts are positive. Source chain transfers include deduplication logic to avoid double-counting transfers that are also captured as destination chain events on Token Terminal tracked chains. All users are classified as 'Sender' type for the product 'axelarnetworkv1'
- **Key fields**: Daily timestamps (`timestamp`), chain identifiers (`chain`), user addresses (`user_address`), user type classification (`user_type`), and product identification (`product_id`)

### Component B: HyperLogLog sketch creation  
- **Purpose**: Converts daily user data into efficient data structures for distinct counting
- **Logic**: Groups daily active users by timestamp, chain, user type, and product ID, then initializes HyperLogLog sketches with precision parameter 15 for each group. This allows memory-efficient storage and computation of distinct user counts across large datasets
- **Key fields**: HyperLogLog sketches (`hll`) containing encoded user sets for each day and dimension combination

### Component C: Rolling window construction
- **Purpose**: Creates 30-day rolling windows for MAU calculation
- **Logic**: Generates a complete datespine covering all days from the earliest data to the current date, ensuring no missing timestamps. For each date in the datespine, creates an array of the 30 preceding days (including the current day). Joins this window definition with the daily HLL data to collect all relevant user sketches for each 30-day period. Uses incremental processing logic to optimize computation for recent time periods
- **Key fields**: Window timestamps (`timestamp`) and associated daily HLL sketches within each 30-day period

### Component D: Dimensional breakdowns
- **Purpose**: Calculates MAU across four different analytical dimensions
- **Logic**: Processes the windowed HLL data to create four separate breakdowns: project-level (aggregating all users regardless of chain or other attributes), chain-level (grouping by individual blockchain), user-type level (grouping by user classification), and product-ID level (grouping by specific product). For each breakdown, merges all HLL sketches within the 30-day window and extracts the distinct user count. Sets unused dimension fields to null for each breakdown type
- **Key fields**: Dimension type (`dimensions`), dimension values (`chain_id`, `user_type`, `product_id`), and calculated MAU counts (`user_mau`)

### Final aggregation
- **Combining components**: Unions all four dimensional breakdowns into a single result set, providing multiple analytical perspectives on the same underlying MAU data
- **Schema standardization**: Applies the `finalize_metric_user_mau` macro to ensure consistent output schema, proper data type handling, and standardized field naming
- **Missing data handling**: Uses zero-filling strategy to populate MAU values for time periods with no user activity, ensuring complete time series coverage
- **Final calculation**: Each MAU value represents the exact count of distinct users who performed at least one Axelar protocol interaction within the corresponding 30-day rolling window, calculated using HyperLogLog merge and extract operations

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

Unique revenue-generating users over a rolling 30-day window.

Axelar NetworkAXL

Archived

Active users (monthly)

Active users (monthly)

Competitive landscape

Chain breakdown