Uniswap Labs collects fees from trades conducted through its interfaces.

Uniswap Labs, established by Hayden Adams in 2018, is a software development company that specializes in creating products for the Uniswap Protocol. This includes the development and maintenance of various applications like the Uniswap web app, a mobile wallet, and an NFT aggregator.

Uniswap Labs acts as a developer and maintainer of the Uniswap Protocol. The company functions independently from the decentralized governance of the protocol.

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Uniswap Labs

# Uniswap Labs Active users (daily) Methodology

## 1. Overview

Daily active users (DAU) for Uniswap Labs measures the number of unique addresses that pay fees to the protocol each day across all supported chains and products. This metric identifies genuine trading activity by tracking fee payments from Uniswap router contracts to designated collector addresses. The methodology captures users across both traditional AMM swaps and UniswapX dutch auction orders, classifying all fee-paying addresses as "Trader" type users. The calculation uses HyperLogLog probabilistic data structures to enable efficient counting across multiple dimensions while maintaining accuracy for large user sets.

## 2. Data sources

- **Token transfer events**: Multi-chain token transfer events from Ethereum, Arbitrum, Base, BSC, Polygon, Optimism, and Avalanche tracking transfers between specific router and collector addresses
- **Transaction records**: Complete transaction data from all supported chains to extract user addresses and validate fee-paying transactions
- **UniswapX events**: Parsed `DutchOrderReactor` `Fill` events from Ethereum to identify UniswapX-specific trading activity and extract swapper addresses
- **Router contract interactions**: Token transfers originating from designated Uniswap router contract addresses across all chains
- **Fee collector data**: Token transfers directed to specific Uniswap Labs fee collector addresses that receive interface fees and protocol fees

## 3. Step-by-step calculation

### Component A: UniswapX transaction identification
- **Purpose**: Identifies users participating in UniswapX dutch auction orders on Ethereum
- **Logic**: Extracts parsed `DutchOrderReactor` `Fill` events from Uniswap v3 Ethereum contracts. Captures the `swapper` address from each fill event along with transaction hash and timestamp. Filters for events from July 1, 2023 onwards to align with fee collection period. Creates a dimension table linking transaction hashes to user addresses for downstream joining.
- **Key fields**: `swapper` address as user identifier, `transaction_hash` for linking, `block_timestamp` for temporal filtering, `chain` set to ethereum, `version` set to v3

### Component B: Dutch auction fee collection
- **Purpose**: Captures fee payments specifically from UniswapX dutch auction orders
- **Logic**: Monitors token transfers directed to hardcoded collector addresses (`0x37a8f295612602f2774d331e562be9e61b83a327`, `0x6460d14dbaeb27aefec8ebef85db35defa31c3b9`) within transactions identified as UniswapX orders. Joins transfer events with the UniswapX transaction allowlist and transaction records to extract user addresses. Applies temporal filtering for July 1, 2023 onwards and excludes one denylisted token address.
- **Key fields**: `user_address` from transaction originator, `token_address` and `amount` of fee payment, `transaction_hash` and `log_index` for deduplication

### Component C: Multi-chain swap fee collection  
- **Purpose**: Captures interface fees from traditional AMM swaps across all supported chains
- **Logic**: Tracks token transfers FROM designated router contract addresses TO specific collector addresses across seven chains. Each chain has its own set of router addresses (universal routers, swap routers) and collector addresses (fee collectors, treasury addresses). Filters transfers for the active fee period from July 1, 2023 to December 25, 2025, when Uniswap Labs disabled interface fees. Joins with transaction data to extract originating user addresses.
- **Key fields**: `from_address` as router identifier, `to_address` as collector identifier, transaction `from_address` as user identifier, transfer `value` as fee amount

### Component D: Fee consolidation and filtering
- **Purpose**: Combines all fee types and applies data quality filters
- **Logic**: Unions Dutch auction fees and swap fees into a single dataset. Removes transfers involving one specific denylisted token address (`0x63b420fb3294ba1d300ce5d3ba4bbca0f4fe5e3b`). Standardizes all records with consistent schema including business classification fields (business line as "Exchange AMM", market sector as "exchanges", business segment as "dex").
- **Key fields**: Unified `user_address`, `token_address`, `amount`, `block_timestamp`, `chain`, and `version` fields

### Component E: Daily user activity aggregation
- **Purpose**: Converts fee payments into daily active user counts
- **Logic**: Truncates all fee payment timestamps to daily boundaries using `timestamp_trunc`. Groups by day, chain, and other dimensional attributes. Extracts unique `user_address` values per day to identify distinct active users. Classifies all fee-paying users as "Trader" type regardless of fee source or amount. Applies chain availability filtering to ensure data quality across supported networks.
- **Key fields**: `timestamp` (daily), `user_dau` containing user addresses, `user_type` set to "Trader", `chain` identifier

### Component F: HyperLogLog sketch creation
- **Purpose**: Enables efficient approximate counting for large user sets across multiple dimensions
- **Logic**: Converts daily user address lists into HyperLogLog sketches using `hll_count.init` with 15-bit precision. Groups sketches by timestamp, chain, user type, and product dimensions. Creates the foundation for cross-dimensional aggregation without double-counting users who appear in multiple categories.
- **Key fields**: `hll` sketch containing compressed user data, dimensional grouping fields for aggregation

### Final aggregation
- **Combining components**: Merges HyperLogLog sketches using `hll_count.merge_partial` and extracts final counts with `hll_count.extract` across four dimensional breakdowns: overall project level, by chain, by user type, and by product. Each breakdown nullifies unused dimensional fields and populates a `dimensions` field indicating the aggregation level.
- **Currency conversion**: Not applicable as this metric counts users rather than monetary values
- **Time aggregation**: Data is truncated to daily boundaries with incremental processing using monthly partitioning for efficiency
- **Final calculation**: The final user DAU value represents the approximate distinct count of unique addresses that paid fees to Uniswap Labs on each day, aggregated across the specified dimensional breakdown. Missing days are filled with zero values, and chain availability filters ensure data completeness across all supported networks.

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

Unique revenue-generating users over a fixed 24-hour window.

Uniswap Labs

Active users (daily)

Active users (daily)

Competitive landscape

Chain breakdown