Collators aggregate parachain transactions block candidates and producing state transition proofs for validators based on those blocks.

Heima is a specialized identity and data verification blockchain powered by Polkadot Relay chain.

HEI holders own and govern the protocol. Heima’s investors include LD Capital, Digital Renaissance, Signum Capital, and others.

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Blockchains (L2)

Heima

# Heima Active addresses (daily) Methodology

## 1. Overview

The Heima active addresses daily metric measures the number of unique addresses that performed transactions on the Heima blockchain network each day. This metric tracks daily blockchain activity by counting distinct user addresses that initiated transactions, providing insights into user engagement and network adoption. The calculation treats daily active users as active addresses, which is appropriate for blockchain analytics where user addresses represent the primary unit of activity measurement.

## 2. Data sources

The methodology uses the following raw blockchain data sources:
- **Heima extrinsics**: Native Heima blockchain transaction records containing transaction sender information and timestamps
- **Heima EVM events**: Parsed events from the Heima EVM ethereum pallet, specifically `Executed` events that contain user address data in event parameters
- **Chain metadata**: Protocol classification data distinguishing between native Heima and Heima EVM chains

## 3. Step-by-step calculation

### Component A: User address extraction
- **Purpose**: Extract unique user addresses from both native Heima and Heima EVM transaction data
- **Logic**: The system processes two distinct data streams. For native Heima extrinsics, user addresses are extracted directly from the `id` field along with block timestamps. For Heima EVM operations, user addresses are extracted from `Executed` events in the ethereum pallet, specifically from the first element of the `event_data` array. All users are classified as "Transaction sender" type, and chains are labeled as either "heima" or "heimaevm" based on the data source
- **Key fields**: `block_timestamp` for timing, `id` or `event_data[0]` for user addresses, chain classification, and user type designation

### Component B: Daily active user calculation  
- **Purpose**: Calculate daily distinct active users by aggregating unique addresses per day
- **Logic**: User addresses are grouped by day using timestamp truncation to daily granularity. The system counts distinct user addresses for each day, creating daily active user records. Incremental processing ensures efficient updates by only processing recent data based on partition boundaries and lookback windows
- **Key fields**: Daily truncated `timestamp`, `user_address` for distinct counting, chain and metadata fields for downstream aggregation

### Component C: Multi-dimensional aggregation
- **Purpose**: Aggregate daily active users across different analytical dimensions using scalable counting methods  
- **Logic**: The system creates HyperLogLog sketches for each user address to enable accurate distinct counting at scale. Daily user data is then aggregated across four dimensions: project-level (project_dbt_tag), chain-level, user type-level, and product-level. HyperLogLog sketches are merged and extracted to produce final distinct counts for each dimension, handling potential address overlaps between different groupings
- **Key fields**: HyperLogLog sketches of `user_address`, dimension classification, aggregated `user_dau` counts

### Final aggregation
- **Combining components**: The active addresses daily metric selects only chain-level and project-level aggregations from the multi-dimensional DAU data, directly mapping `user_dau` values to `active_addresses_daily`
- **Currency conversion**: No currency conversion required as this is a count-based metric
- **Time aggregation**: Data is aggregated at daily boundaries using timestamp truncation, with missing days filled with zero values
- **Final calculation**: The final active addresses daily value equals the distinct count of user addresses that performed transactions on each day, calculated using HyperLogLog probabilistic counting for accuracy and scalability

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

Unique active addresses over a fixed 24-hour window.

HeimaHEI

Active addresses (daily)

Active addresses (daily)

Competitive landscape

Chain breakdown