Liquidity providers deposit funds into Thena and stake their LP tokens to receive THE tokens (token incentives).

Thena is a non-custodial exchange protocol built on BNB Chain. Thena was founded by an anonymous team and launched in 2023.

THE tokenholders own and govern the protocol. They vote for pools where they wish to receive trading fees and external bribes from, while pools receive THE emissions in respect to their share of votes.

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Exchanges (DEX)

Thena

# Thena Active users (monthly) Methodology

## 1. Overview

The Monthly Active Users (MAU) metric measures the number of unique users who have performed trading activity on Thena DEX over rolling 30-day periods. This metric answers the business question "How many distinct users are actively trading on Thena's decentralized exchange over the past month?" The calculation uses HyperLogLog data structures to efficiently count distinct users across multiple protocol versions, chains, and time windows, providing dimensional breakdowns by project, chain, user type, and product.

## 2. Data sources

The MAU calculation draws from several blockchain data sources:

- **Swap events**: Parsed `Swap` events from Thena V1 (`Pair_Swap_event`), V2 (`AlgebraPool_Swap_event`), and V3 (`AlgebraPoolV2_Swap_event`) smart contracts across BSC and opBNB chains
- **Transaction data**: BSC and opBNB transaction records containing the `from_address` field to identify the actual users initiating trades
- **Protocol versions**: Data from three versions of Thena DEX with different smart contract architectures and event schemas
- **Chain coverage**: Multi-chain data spanning BSC (Binance Smart Chain) and opBNB networks

## 3. Step-by-step calculation

### Component A: Trade event extraction
- **Purpose**: Extracts and standardizes swap events across all Thena protocol versions and chains
- **Logic**: The system processes three distinct protocol versions with different event schemas. For V1, it extracts `Pair_Swap_event` data from BSC and opBNB chains, calculating token amounts using `amount0In`, `amount0Out`, `amount1In`, and `amount1Out` fields. For V2, it processes `AlgebraPool_Swap_event` data with direct `amount0` and `amount1` fields. For V3, it handles `AlgebraPoolV2_Swap_event` data including fee information via the `overrideFee` field. Each event is joined with transaction records to identify the user address from the `from_address` field
- **Key fields**: `block_timestamp`, `transaction_hash`, `log_index`, `user_address` (from transaction `from_address`), token amounts, and protocol version identifiers

### Component B: Daily active user aggregation  
- **Purpose**: Creates daily snapshots of unique active users with dimensional attributes
- **Logic**: The system groups swap events by day using `timestamp_trunc` on `block_timestamp`, creating daily buckets. Each user who performed at least one trade on a given day is counted as an active user. Users are classified as 'Trader' type, and the data includes dimensional attributes like `chain`, `product_id` (Thena V1, Thena Fusion, Thena Integral), and business categorization fields
- **Key fields**: `timestamp` (daily), `user_address`, `chain`, `user_type`, `product_id`

### Component C: HyperLogLog initialization
- **Purpose**: Converts daily user sets into HyperLogLog data structures for efficient distinct counting
- **Logic**: Each day's set of unique users is converted into an HLL sketch using `hll_count.init` with 15-bit precision. This probabilistic data structure enables efficient merging of user sets across time periods without storing actual user addresses. The system groups by timestamp, chain, user type, and product to create separate HLL sketches for each dimensional combination
- **Key fields**: HLL sketches containing compressed representations of daily user sets

### Component D: Date spine and rolling window creation
- **Purpose**: Creates complete date coverage and establishes 30-day rolling windows for MAU calculation
- **Logic**: A date spine is generated covering the full analysis period using `generate_timestamp_array` with daily intervals. For each date in the spine, the system creates a 30-day rolling window by generating an array of the current date plus the previous 29 days using `timestamp_sub(interval 29 day)`. This ensures that every day has a complete 30-day lookback period, even if some days had no trading activity
- **Key fields**: `timestamp` (target date), `joinday` (dates within the 30-day window)

### Component E: HLL merging and MAU calculation
- **Purpose**: Merges HLL sketches across 30-day windows to calculate monthly active users
- **Logic**: For each target date, the system identifies all HLL sketches from the corresponding 30-day window and merges them using `hll_count.merge_partial`. The merged HLL is then converted to a distinct count estimate using `hll_count.extract`. This process efficiently calculates the number of unique users who were active at any point during the 30-day period without double-counting users who were active on multiple days
- **Key fields**: Merged HLL sketches, extracted `user_mau` counts

### Final aggregation
- **Combining components**: The system generates four separate dimensional breakdowns from the merged HLL data: project-level (all dimensions collapsed), chain-level (grouped by `chain_id`), user-type-level (grouped by `user_type`), and product-level (grouped by `product_id`). These breakdowns are combined using `union all` operations
- **Currency conversion**: No currency conversion is applied as this is a user count metric
- **Time aggregation**: The metric uses rolling 30-day windows calculated daily, meaning each day shows the count of unique users active over the past 30 days including that day
- **Final calculation**: The final MAU value represents the estimated distinct count of users who performed at least one trade on Thena DEX during any day within the 30-day rolling window, calculated using probabilistic HyperLogLog merging for computational efficiency

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

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

ThenaTHE

Archived

Active users (monthly)

Active users (monthly)

Competitive landscape

Chain breakdown