# zkSync Era Active addresses (daily) Methodology

## 1. Overview

The zkSync Era active addresses daily metric counts the number of unique addresses that initiated at least one transaction on the zkSync Era network each day. This metric serves as a key indicator of daily user activity and network adoption. The calculation identifies all transaction senders from raw blockchain data and counts unique addresses per day using HyperLogLog aggregation for efficiency.

## 2. Data sources

- **zkSync Era transaction records**: Raw blockchain transaction data containing sender addresses, timestamps, and transaction metadata
- **Chain availability configuration**: Data quality and availability filters to ensure reliable metric calculation periods

## 3. Step-by-step calculation

### Component A: User identification
- **Purpose**: Extract all transaction senders from zkSync Era blockchain data
- **Logic**: From raw zkSync Era transaction records, extract all sender addresses (`from_address`) along with block timestamps and transaction hashes. Each transaction sender is classified as a user with the type "Transaction sender". The data includes chain classification as 'zksyncera', market sector as 'blockchains_l2', and business segment as 'blockchain'. Product ID is set to null as this represents chain-level activity rather than specific application usage.
- **Key fields**: `block_timestamp` for timing, `from_address` as the user identifier, `transaction_hash` for deduplication, and classification metadata

### Component B: Daily user deduplication
- **Purpose**: Create unique user-day combinations to avoid double-counting active users
- **Logic**: Group the user data by truncating timestamps to day level and taking distinct combinations of date, chain, user type, and user address. This ensures that users who made multiple transactions on the same day are only counted once. The process maintains metadata fields including market sector, business segment, and product identifiers.
- **Key fields**: `timestamp` (truncated to day), `user_address` for uniqueness, `chain`, `user_type`, and metadata fields

### Component C: HyperLogLog aggregation
- **Purpose**: Efficiently count unique users across multiple dimension breakdowns
- **Logic**: Create HyperLogLog sketches for each day-chain-user_type-product combination to enable approximate counting of unique users. The HLL sketches are then merged and extracted to produce counts across different dimension breakdowns: overall project level ('project_dbt_tag'), chain level ('chain'), user type level ('user_type'), and product level ('product_id'). This approach allows for efficient aggregation while maintaining accuracy for large datasets.
- **Key fields**: `user_dau` as the unique user count, `dimensions` to identify the aggregation level, `timestamp_grain` set to 'day'

### Component D: Active addresses selection
- **Purpose**: Filter the user DAU data to create the active addresses metric
- **Logic**: From the multi-dimensional user DAU aggregations, select only the 'chain' and 'project_dbt_tag' dimensions which represent the relevant breakdowns for active addresses reporting. Rename the `user_dau` field to `active_addresses_daily` to reflect the specific metric being calculated.
- **Key fields**: `active_addresses_daily` as the final count, `dimensions` for breakdown identification, `chain_id` for chain-level reporting

### Final aggregation
- **Combining components**: The active addresses metric is derived directly from the user DAU calculation by filtering to specific dimensions and renaming the metric field
- **Currency conversion**: Not applicable as this metric counts addresses rather than monetary values
- **Time aggregation**: Data is aggregated to daily boundaries using day-level timestamp truncation
- **Final calculation**: The final metric value represents the count of unique addresses that initiated at least one transaction on zkSync Era for each day, broken down by overall project and chain level dimensions. Missing days are filled with zeros to maintain time series continuity, and chain availability filters ensure data quality standards are met.

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

Unique active addresses over a fixed 24-hour window.

Active addresses (daily)

zkSync Era

zkSync Era batches users' transactions and submits them to Ethereum together with a zero-knowledge proof, paying a share of the transaction fees to Ethereum validators (expense).

zkSync Era is an L2 smart contract platform for decentralized applications on Ethereum. zkSync Era was founded by Matter Labs and launched in 2023.

Matter Labs team owns and governs the protocol. Matter Labs' investors include a16z, Lightspeed Venture Partners, Blockchain Capital, etc.

zkSync EraZK

Active addresses (daily)

Active addresses (daily)

Competitive landscape

Chain breakdown