Miners process transactions and receive fees from users (supply-side fees).

Bitcoin is a distributed ledger for transfer and store of value (a blockchain). Bitcoin was founded by a pseudonym Satoshi Nakamoto and launched in 2009.

BTC holders own and govern the protocol. They currently do not take a cut of the total transaction fees paid by users (revenue).

github

block explorer

Blockchains (L1)

Bitcoin

# Bitcoin Active addresses (daily) Methodology

## 1. Overview

Bitcoin daily active addresses measures the number of unique Bitcoin addresses that initiated at least one transaction on a given day. This metric provides insight into Bitcoin network usage by counting distinct transaction senders rather than transaction volume. The calculation leverages Bitcoin's UTXO (Unspent Transaction Output) model to resolve input addresses by tracing them back to the outputs they reference, enabling accurate identification of transaction initiators.

## 2. Data sources

- **Bitcoin blockchain transactions**: Raw Bitcoin transaction records containing input and output data from the Bitcoin network
- **Transaction inputs**: Records of previous transaction outputs being spent, containing references to prior transaction hashes and output indexes
- **Transaction outputs**: Records of new Bitcoin outputs created, containing `scriptPubKey` address information for recipients
- **Address resolution data**: Derived lookup tables mapping transaction outputs to their associated Bitcoin addresses

## 3. Step-by-step calculation

### Component A: Output address resolution
- **Purpose**: Creates a lookup table mapping Bitcoin transaction outputs to their associated addresses
- **Logic**: Processes raw Bitcoin transactions and extracts the `address` field from each output's `scriptPubKey` structure. Each output is indexed by its transaction hash and output index position within that transaction. This creates a comprehensive mapping that can later be used to resolve which addresses were involved when these outputs are spent as inputs in subsequent transactions.
- **Key fields**: `transaction_hash`, `output_index`, `user_address`, `block_timestamp`

### Component B: Input address resolution (historical data)
- **Purpose**: Resolves sender addresses for Bitcoin transactions processed before 2019-01-01
- **Logic**: Takes transaction inputs and resolves the actual sender addresses using the output address lookup table. Each input references a previous transaction output via `input_transaction_hash` and `input_output_index`. By joining with the output address mapping, determines which address originally controlled the Bitcoin being spent. Groups results by day to identify unique active addresses.
- **Key fields**: `timestamp` (daily), `user_address`

### Component C: Input address resolution (recent data)
- **Purpose**: Resolves sender addresses for Bitcoin transactions from 2019-01-01 onwards using incremental processing
- **Logic**: Applies the same input address resolution logic as historical data but uses incremental updates to process only new transactions. Maintains a lookback period for reprocessing recent data to handle potential reorganizations or late-arriving data. Groups results by day to identify unique active addresses.
- **Key fields**: `timestamp` (daily), `user_address`

### Component D: User DAU compilation
- **Purpose**: Combines historical and recent user address data into a unified daily active user dataset
- **Logic**: Unions the historical and recent address resolution datasets, labeling all resolved addresses as "Transaction sender" user type. Creates a complete time series of daily Bitcoin addresses that initiated transactions, forming the basis for active address counting.
- **Key fields**: `timestamp`, `timestamp_grain`, `chain`, `user_type`, `user_address`

### Component E: HyperLogLog aggregation
- **Purpose**: Counts unique addresses per day using probabilistic data structures for efficient processing
- **Logic**: Applies HyperLogLog sketching to count distinct addresses across multiple dimensional breakdowns. Initializes HyperLogLog sketches for each address using `hll_count.init()` with 15-bit precision. Merges sketches using `hll_count.merge_partial()` and extracts final unique counts using `hll_count.extract()`. Creates breakdowns by chain level, project level, and user type level to support different reporting requirements.
- **Key fields**: `timestamp`, `dimensions`, `chain_id`, `user_dau`

### Final aggregation
- **Combining components**: Takes the aggregated user DAU data and filters for chain-level and project-level dimensions, then renames the `user_dau` field to `active_addresses_daily` to match the target metric schema
- **Currency conversion**: Not applicable for this address counting metric
- **Time aggregation**: Daily boundaries are established using timestamp truncation to day level, ensuring consistent daily counting periods
- **Final calculation**: The final active addresses count represents the unique number of Bitcoin addresses that sent at least one transaction on each day, calculated using HyperLogLog probabilistic counting for accuracy and efficiency across the complete Bitcoin transaction history

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

Unique active addresses over a fixed 24-hour window.

BitcoinBTC

Active addresses (daily)

Active addresses (daily)

Competitive landscape